Nigral volume loss in prodromal, early, and moderate Parkinson's disease.

The loss of melanized neurons in the substantia nigra pars compacta (SNc) is a hallmark pathology in Parkinson's disease (PD). Melanized neurons in SNc can be visualized in vivo using magnetization transfer (MT) effects. Nigral volume was extracted in data acquired with a MT-prepared gradient echo sequence in 33 controls, 83 non-manifest carriers (42 LRRK2 and 41 GBA nonmanifest carriers), 65 prodromal hyposmic participants, 105 de novo PD patients and 26 48-month PD patients from the Parkinson's Progressive Markers Initiative. No difference in nigral volume was seen between controls and LRRK2 and GBA non-manifest carriers (F=0.076; P=0.927). A significant main effect in group was observed between controls, prodromal hyposmic participants, and overt PD patients (F=5.192; P=0.002). Longer disease duration significantly correlated with lower nigral volume (r=-0.252; P=0.010). This study shows that nigral depigmentation can be robustly detected in prodromal hyposmic participants and overt PD patients.

Neuromelanin-sensitive MRI correlates of cognitive and motor function in Parkinson's disease with freezing of gait.

Substantia nigra pars compacta (SNc) and locus coeruleus (LC) are neuromelanin-rich nuclei implicated in diverse cognitive and motor processes in normal brain function and disease. However, their roles in aging and neurodegenerative disease mechanisms have remained unclear due to a lack of tools to study them in vivo. Preclinical and post-mortem human investigations indicate that the relationship between tissue neuromelanin content and neurodegeneration is complex. Neuromelanin exhibits both neuroprotective and cytotoxic characteristics, and tissue neuromelanin content varies across the lifespan, exhibiting an inverted U-shaped relationship with age. Neuromelanin-sensitive MRI (NM-MRI) is an emerging modality that allows measurement of neuromelanin-associated contrast in SNc and LC in humans. NM-MRI robustly detects disease effects in these structures in neurodegenerative and psychiatric conditions, including Parkinson's disease (PD). Previous NM-MRI studies of PD have largely focused on detecting disease group effects, but few studies have reported NM-MRI correlations with phenotype. Because neuromelanin dynamics are complex, we hypothesize that they are best interpreted in the context of both disease stage and aging, with neuromelanin loss correlating with symptoms most clearly in advanced stages where neuromelanin loss and neurodegeneration are coupled. We tested this hypothesis using NM-MRI to measure SNc and LC volumes in healthy older adult control individuals and in PD patients with and without freezing of gait (FOG), a severe and disabling PD symptom. We assessed for group differences and correlations between NM-MRI measures and aging, cognition and motor deficits. SNc volume was significantly decreased in PD with FOG compared to controls. SNc volume correlated significantly with motor symptoms and cognitive measures in PD with FOG, but not in PD without FOG. SNc volume correlated significantly with aging in PD. When PD patients were stratified by disease duration, SNc volume correlated with aging, cognition, and motor deficits only in PD with disease duration >5 years. We conclude that in severe or advanced PD, identified by either FOG or disease duration >5 years, the observed correlations between SNc volume and aging, cognition, and motor function may reflect the coupling of neuromelanin loss with neurodegeneration and the associated emergence of a linear relationship between NM-MRI measures and phenotype.

In vivo detection of substantia nigra and locus coeruleus volume loss in Parkinson's disease using neuromelanin-sensitive MRI: Replication in two cohorts.

Patients with Parkinson's disease undergo a loss of melanized neurons in substantia nigra pars compacta and locus coeruleus. Very few studies have assessed substantia nigra pars compacta and locus coeruleus pathology in Parkinson's disease simultaneously with magnetic resonance imaging (MRI). Neuromelanin-sensitive MRI measures of substantia nigra pars compacta and locus coeruleus volume based on explicit magnetization transfer contrast have been shown to have high scan-rescan reproducibility in controls, but no study has replicated detection of Parkinson's disease-associated volume loss in substantia nigra pars compacta and locus coeruleus in multiple cohorts with the same methodology. Two separate cohorts of Parkinson's disease patients and controls were recruited from the Emory Movement Disorders Clinic and scanned on two different MRI scanners. In cohort 1, imaging data from 19 controls and 22 Parkinson's disease patients were acquired with a Siemens Trio 3 Tesla scanner using a 2D gradient echo sequence with magnetization transfer preparation pulse. Cohort 2 consisted of 33 controls and 39 Parkinson's disease patients who were scanned on a Siemens Prisma 3 Tesla scanner with a similar imaging protocol. Locus coeruleus and substantia nigra pars compacta volumes were segmented in both cohorts. Substantia nigra pars compacta volume (Cohort 1: p = 0.0148; Cohort 2: p = 0.0011) and locus coeruleus volume (Cohort 1: p = 0.0412; Cohort 2: p = 0.0056) were significantly reduced in the Parkinson's disease group as compared to controls in both cohorts. This imaging approach robustly detects Parkinson's disease effects on these structures, indicating that it is a promising marker for neurodegenerative neuromelanin loss.

Nigral volumetric and microstructural measures in individuals with scans without evidence of dopaminergic deficit.

Introduction: Striatal dopamine transporter (DAT) imaging using 123I-ioflupane single photon positron emitted computed tomography (SPECT) (DaTScan, GE) identifies 5-20% of newly diagnosed Parkinson's disease (PD) subjects enrolling in clinical studies to have scans without evidence of dopaminergic deficit (SWEDD). These individuals meet diagnostic criteria for PD, but do not clinically progress as expected, and they are not believed to have neurodegenerative Parkinsonism. Inclusion of SWEDD participants in PD biomarker studies or therapeutic trials may therefore cause them to fail. DaTScan can identify SWEDD individuals, but it is expensive and not widely available; an alternative imaging approach is needed. Here, we evaluate the use of neuromelanin-sensitive, iron-sensitive, and diffusion contrasts in substantia nigra pars compacta (SNpc) to differentiate SWEDD from PD individuals. Methods: Neuromelanin-sensitive, iron-sensitive, and diffusion imaging data for SWEDD, PD, and control subjects were downloaded from the Parkinson's progression markers initiative (PPMI) database. SNpc volume, SNpc iron (R 2), and SNpc free water (FW) were measured for each participant. Results: Significantly smaller SNpc volume was seen in PD as compared to SWEDD (P < 10-3) and control (P < 10-3) subjects. SNpc FW was elevated in the PD group relative to controls (P = 0.017). No group difference was observed in SNpc R 2. Conclusion: In conclusion, nigral volume and FW in the SWEDD group were similar to that of controls, while a reduction in nigral volume and increased FW were observed in the PD group relative to SWEDD and control participants. These results suggest that these MRI measures should be explored as a cost-effective alternative to DaTScan for evaluation of the nigrostriatal system.

Associations between Cortical Thickness and Metamemory in Alzheimer's Disease.

Metacognitive deficits affect Alzheimer's disease (AD) patient safety and increase caregiver burden. The brain areas that support metacognition are not well understood. 112 participants from the Imaging and Genetic Biomarkers for AD (ImaGene) study underwent comprehensive cognitive testing and brain magnetic resonance imaging. A performance-prediction paradigm was used to evaluate metacognitive abilities for California Verbal Learning Test-II learning (CVLT-II 1-5) and delayed recall (CVLT-II DR); Visual Reproduction-I immediate recall (VR-I Copy) and Visual Reproduction-II delayed recall (VR-II DR); Rey-Osterrieth Complex Figure Copy (Rey-O Copy) and delayed recall (Rey-O DR). Vertex-wise multivariable regression of cortical thickness was performed using metacognitive scores as predictors while controlling for age, sex, education, and intracranial volume. Subjects who overestimated CVLT-II DR in prediction showed cortical atrophy, most pronounced in the bilateral temporal and left greater than right (L > R) frontal cortices. Overestimation of CVLT-II 1-5 prediction and DR performance in postdiction showed L > R associations with medial, inferior and lateral temporal and left posterior cingulate cortical atrophy. Overconfident prediction of VR-I Copy performance was associated with right greater than left medial, inferior and lateral temporal, lateral parietal, anterior and posterior cingulate and lateral frontal cortical atrophy. Underestimation of Rey-O Copy performance in prediction was associated with atrophy localizing to the temporal and cingulate areas, and in postdiction, with diffuse cortical atrophy. Impaired metacognition was associated to cortical atrophy. Our results indicate that poor insight into one's cognitive abilities is a pervasive neurodegenerative feature associated with AD across the cognitive spectrum.

Efficient population modification gene-drive rescue system in the malaria mosquito Anopheles stephensi.

Cas9/gRNA-mediated gene-drive systems have advanced development of genetic technologies for controlling vector-borne pathogen transmission. These technologies include population suppression approaches, genetic analogs of insecticidal techniques that reduce the number of insect vectors, and population modification (replacement/alteration) approaches, which interfere with competence to transmit pathogens. Here, we develop a recoded gene-drive rescue system for population modification of the malaria vector, Anopheles stephensi, that relieves the load in females caused by integration of the drive into the kynurenine hydroxylase gene by rescuing its function. Non-functional resistant alleles are eliminated via a dominantly-acting maternal effect combined with slower-acting standard negative selection, and rare functional resistant alleles do not prevent drive invasion. Small cage trials show that single releases of gene-drive males robustly result in efficient population modification with ≥95% of mosquitoes carrying the drive within 5-11 generations over a range of initial release ratios.

Experimental population modification of the malaria vector mosquito, Anopheles stephensi.

Small laboratory cage trials of non-drive and gene-drive strains of the Asian malaria vector mosquito, Anopheles stephensi, were used to investigate release ratios and other strain properties for their impact on transgene spread during simulated population modification. We evaluated the effects of transgenes on survival, male contributions to next-generation populations, female reproductive success and the impact of accumulation of gene drive-resistant genomic target sites resulting from nonhomologous end-joining (NHEJ) mutagenesis during Cas9, guide RNA-mediated cleavage. Experiments with a non-drive, autosomally-linked malaria-resistance gene cassette showed 'full introduction' (100% of the insects have at least one copy of the transgene) within 8 weeks (≤ 3 generations) following weekly releases of 10:1 transgenic:wild-type males in an overlapping generation trial design. Male release ratios of 1:1 resulted in cages where mosquitoes with at least one copy of the transgene fluctuated around 50%. In comparison, two of three cages in which the malaria-resistance genes were linked to a gene-drive system in an overlapping generation, single 1:1 release reached full introduction in 6-8 generations with a third cage at ~80% within the same time. Release ratios of 0.1:1 failed to establish the transgenes. A non-overlapping generation, single-release trial of the same gene-drive strain resulted in two of three cages reaching 100% introduction within 6-12 generations following a 1:1 transgenic:wild-type male release. Two of three cages with 0.33:1 transgenic:wild-type male single releases achieved full introduction in 13-16 generations. All populations exhibiting full introduction went extinct within three generations due to a significant load on females having disruptions of both copies of the target gene, kynurenine hydroxylase. While repeated releases of high-ratio (10:1) non-drive constructs could achieve full introduction, results from the 1:1 release ratios across all experimental designs favor the use of gene drive, both for efficiency and anticipated cost of the control programs.

Association of brain amyloidosis with the incidence and frequency of neuropsychiatric symptoms in ADNI: a multisite observational cohort study.

OBJECTIVE: To investigate the relationship between amyloid burden and frequency of existing and incidence of new neuropsychiatric symptoms (NPS) in elderly with and without cognitive decline. METHODS: 275 cognitively normal controls (NC), 100 subjective memory complaint (SMC), 559 mild cognitive impairment (MCI) and 143 Alzheimer's disease dementia subjects from the Alzheimer's Disease Neuroimaging Initiative received (18F)-florbetapir positron emission tomography (PET) scans. Yearly neuropsychiatric inventory (Neuropsychiatric Inventory (NPI)/NPI-Questionnaire) data were collected from the study partners at each visit. Mean standard uptake volume ratios (SUVR) normalised to whole cerebellum were obtained. Positive amyloid PET scan was defined as mean SUVR ≥1.17. Fisher's exact test was used to compare frequency and incidence between amyloid positive and amyloid negative subjects. Survival analyses were used to estimate of neuropsychiatric symptoms (NPS) between amyloid positive and amyloid negative subjects. Survival analyses were used to estimate hazard ratios for developing the most common NPS by amyloid status. RESULTS: No differences in NPS frequency were seen between amyloid positive and amyloid negative NC, SMC, MCI or dementia groups. MCI subjects with amyloid pathology however tended to have greater frequency x severity (FxS) of anxiety, hallucinations, delusions, apathy, disinhibition, irritability, aberrant motor behavior, and appetite, but not agitation, depression, night-time disturbances, or elation. MCI subjects with amyloid pathology were at greater risk for developing apathy, anxiety and agitation over time. Baseline presence of agitation and apathy and new onset agitation, irritability and apathy predicted faster conversion to dementia among MCI subjects. CONCLUSIONS: Amyloid pathology is associated with greater rate of development of new NPS in MCI. Anxiety and delusions are significant predictors of amyloid pathology. Agitation, irritability and apathy are significant predictors for conversion from MCI to dementia.

Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment.

We analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors.

Automated and manual hippocampal segmentation techniques: Comparison of results, reproducibility and clinical applicability.

BACKGROUND: Imaging techniques used to measure hippocampal atrophy are key to understanding the clinical progression of Alzheimer's disease (AD). Various semi-automated hippocampal segmentation techniques are available and require human expert input to learn how to accurately segment new data. Our goal was to compare 1) the performance of our automated hippocampal segmentation technique relative to manual segmentations, and 2) the performance of our automated technique when provided with a training set from two different raters. We also explored the ability of hippocampal volumes obtained using manual and automated hippocampal segmentations to predict conversion from MCI to AD. METHODS: We analyzed 161 1.5 T T1-weighted brain magnetic resonance images (MRI) from the ADCS Donepezil/Vitamin E clinical study. All subjects carried a diagnosis of mild cognitive impairment (MCI). Three different segmentation outputs (one produced by manual tracing and two produced by a semi-automated algorithm trained with training sets developed by two raters) were compared using single measure intraclass correlation statistics (smICC). The radial distance method was used to assess each segmentation technique's ability to detect hippocampal atrophy in 3D. We then compared how well each segmentation method detected baseline hippocampal differences between MCI subjects who remained stable (MCInc) and those who converted to AD (MCIc) during the trial. Our statistical maps were corrected for multiple comparisons using permutation-based statistics with a threshold of p < .01. RESULTS: Our smICC analyses showed significant agreement between the manual and automated hippocampal segmentations from rater 1 [right smICC = 0.78 (95%CI 0.72-0.84); left smICC = 0.79 (95%CI 0.72-0.85)], the manual segmentations from rater 1 versus the automated segmentations from rater 2 [right smICC = 0.78 (95%CI 0.7-0.84); left smICC = 0.78 (95%CI 0.71-0.84)], and the automated segmentations of rater 1 versus rater 2 [right smICC = 0.97 (95%CI 0.96-0.98); left smICC = 0.97 (95%CI 0.96-0.98)]. All three segmentation methods detected significant CA1 and subicular atrophy in MCIc compared to MCInc at baseline (manual: right pcorrected = 0.0112, left pcorrected = 0.0006; automated rater 1: right pcorrected = 0.0318, left pcorrected = 0.0302; automated rater 2: right pcorrected = 0.0029, left pcorrected = 0.0166). CONCLUSIONS: The hippocampal volumes obtained with a fast semi-automated segmentation method were highly comparable to the ones obtained with the labor-intensive manual segmentation method. The AdaBoost automated hippocampal segmentation technique is highly reliable allowing the efficient analysis of large data sets.

A comparison of theoretical and statistically derived indices for predicting cognitive decline.

INTRODUCTION: Both theoretical and statistically derived approaches have been used in research settings for predicting cognitive decline. METHODS: Fifty-eight cognitively normal (NC) and 71 mild cognitive impairment (MCI) subjects completed a comprehensive cognitive battery for up to 5 years of follow-up. Composite indices of cognitive function were derived using a classic theoretical approach and exploratory factor analysis (EFA). Cognitive variables comprising each factor were averaged to form the EFA composite indices. Logistic regression was used to investigate whether these cognitive composites can reliably predict cognitive outcomes. RESULTS: Neither method predicted decline in NC. The theoretical memory, executive, attention, and language composites and the EFA-derived "attention/executive" and "verbal memory" composites were significant predictors of decline in MCI. The best models achieved an area under the curve of 0.94 in MCI. CONCLUSIONS: The theoretical and the statistically derived cognitive composite approaches are useful in predicting decline in MCI but not in NC.

Dance Experience and Associations with Cortical Gray Matter Thickness in the Aging Population.

INTRODUCTION: We investigated the effect dance experience may have on cortical gray matter thickness and cognitive performance in elderly participants with and without mild cognitive impairment (MCI). METHODS: 39 cognitively normal and 48 MCI elderly participants completed a questionnaire regarding their lifetime experience with music, dance, and song. Participants identified themselves as either dancers or nondancers. All participants received structural 1.5-tesla MRI scans and detailed clinical and neuropsychological evaluations. An advanced 3D cortical mapping technique was then applied to calculate cortical thickness. RESULTS: Despite having a trend-level significantly thinner cortex, dancers performed better in cognitive tasks involving learning and memory, such as the California Verbal Learning Test-II (CVLT-II) short delay free recall (p = 0.004), the CVLT-II long delay free recall (p = 0.003), and the CVLT-II learning over trials 1-5 (p = 0.001). DISCUSSION: Together, these results suggest that dance may result in an enhancement of cognitive reserve in aging, which may help avert or delay MCI.

Novel verbal fluency scores and structural brain imaging for prediction of cognitive outcome in mild cognitive impairment.

INTRODUCTION: The objective of this study was to assess the utility of novel verbal fluency scores for predicting conversion from mild cognitive impairment (MCI) to clinical Alzheimer's disease (AD). METHOD: Verbal fluency lists (animals, vegetables, F, A, and S) from 107 MCI patients and 51 cognitively normal controls were transcribed into electronic text files and automatically scored with traditional raw scores and five types of novel scores computed using methods from machine learning and natural language processing. Additional scores were derived from structural MRI scans: region of interest measures of hippocampal and ventricular volumes and gray matter scores derived from performing ICA on measures of cortical thickness. Over 4 years of follow-up, 24 MCI patients converted to AD. Using conversion as the outcome variable, ensemble classifiers were constructed by training classifiers on the individual groups of scores and then entering predictions from the primary classifiers into regularized logistic regression models. Receiver operating characteristic curves were plotted, and the area under the curve (AUC) was measured for classifiers trained with five groups of available variables. RESULTS: Classifiers trained with novel scores outperformed those trained with raw scores (AUC 0.872 vs 0.735; P < .05 by DeLong test). Addition of structural brain measurements did not improve performance based on novel scores alone. CONCLUSION: The brevity and cost profile of verbal fluency tasks recommends their use for clinical decision making. The word lists generated are a rich source of information for predicting outcomes in MCI. Further work is needed to assess the utility of verbal fluency for early AD.

Common variants in ABCA7 and MS4A6A are associated with cortical and hippocampal atrophy.

The precise physiologic function of many of the recently discovered Alzheimer's disease risk variants remains unknown. The downstream effects of genetic variants remain largely unexplored. We studied the relationship between the top 10 non-APOE genes with cortical and hippocampal atrophy as markers of neurodegeneration using 1.5T magnetic resonance imaging, 1-million single nucleotide polymorphism Illumina Human Omni-Quad array and Illumina Human BeadChip peripheral blood expression array data on 50 cognitively normal and 98 mild cognitive impairment subjects. After explicit matching of cortical and hippocampal morphology, we computed in 3D, the cortical thickness and hippocampal radial distance measures for each participant. Associations between the top 10 non-APOE genome-wide hits and neurodegeneration were explored using linear regression. Map-wise statistical significance was determined with permutations using threshold of p < 0.01. MS4A6A rs610932 and ABCA7 rs3764650 demonstrated significant associations with cortical and hippocampal atrophy. Exploratory MS4A6A and ABCA7 peripheral blood expression analyses revealed a similar pattern of associations with cortical neurodegeneration. To our knowledge, this is the first report of the effect of ABCA7 and MS4A6A on neurodegeneration.

Plasma BDNF levels associate with Pittsburgh compound B binding in the brain.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) plays an important role in Alzheimer's disease (AD) and other neurodegenerative disorders. BDNF function is adversely affected by amyloid beta (Aß) in AD. BDNF levels in brain and peripheral tissues are lower in patients with AD and MCI, than in controls. Here we examined the association between plasma levels of BDNF and amyloid deposition in the brain measured with Pittsburgh Compound B (PiB). METHOD: Our dataset consisted of 18 AD, 56 mild cognitive impairment (MCI) and 3 normal control (NC) Alzheimer's Disease Neuroimaging Initiative-1 (ADNI1) subjects with available [11C] PiB and peripheral blood protein data. MRI-coregistered PET data was smoothed with a 15 mm kernel and mapped onto 3D hemispheric models using the warping deformations computed in cortical pattern matching of the associated MRI scans. We applied linear regression to examine in 3D the associations between BDNF and PiB SUVR, while adjusting for age and sex. We used permutation statistics thresholded at p<0.01 for multiple comparisons correction. RESULTS: Plasma BDNF levels showed significant negative associations with left greater than right amyloid burden in the lateral temporal, inferior parietal, inferior frontal, anterior and posterior cingulate, and orbitofrontal regions (left pcorrected=0.03). CONCLUSIONS: As hypothesized, lower plasma levels of BDNF were significantly associated with widespread brain amyloidosis.

Brain amyloidosis ascertainment from cognitive, imaging, and peripheral blood protein measures.

BACKGROUND: The goal of this study was to identify a clinical biomarker signature of brain amyloidosis in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) mild cognitive impairment (MCI) cohort. METHODS: We developed a multimodal biomarker classifier for predicting brain amyloidosis using cognitive, imaging, and peripheral blood protein ADNI1 MCI data. We used CSF ß-amyloid 1-42 (Aß42) ≤ 192 pg/mL as proxy measure for Pittsburgh compound B (PiB)-PET standard uptake value ratio ≥ 1.5. We trained our classifier in the subcohort with CSF Aß42 but no PiB-PET data and tested its performance in the subcohort with PiB-PET but no CSF Aß42 data. We also examined the utility of our biomarker signature for predicting disease progression from MCI to Alzheimer dementia. RESULTS: The CSF training classifier selected Mini-Mental State Examination, Trails B, Auditory Verbal Learning Test delayed recall, education, APOE genotype, interleukin 6 receptor, clusterin, and ApoE protein, and achieved leave-one-out accuracy of 85% (area under the curve [AUC] = 0.8). The PiB testing classifier achieved an AUC of 0.72, and when classifier self-tuning was allowed, AUC = 0.74. The 36-month disease-progression classifier achieved AUC = 0.75 and accuracy = 71%. CONCLUSIONS: Automated classifiers based on cognitive and peripheral blood protein variables can identify the presence of brain amyloidosis with a modest level of accuracy. Such methods could have implications for clinical trial design and enrollment in the near future. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that a classification algorithm based on cognitive, imaging, and peripheral blood protein measures identifies patients with brain amyloid on PiB-PET with moderate accuracy (sensitivity 68%, specificity 78%).

Alzheimer risk genes modulate the relationship between plasma apoE and cortical PiB binding.

OBJECTIVE: We investigated the association between apoE protein plasma levels and brain amyloidosis and the effect of the top 10 Alzheimer disease (AD) risk genes on this association. METHODS: Our dataset consisted of 18 AD, 52 mild cognitive impairment, and 3 cognitively normal Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) participants with available [(11)C]-Pittsburgh compound B (PiB) and peripheral blood protein data. We used cortical pattern matching to study associations between plasma apoE and cortical PiB binding and the effect of carrier status for the top 10 AD risk genes. RESULTS: Low plasma apoE was significantly associated with high PiB SUVR, except in the sensorimotor and entorhinal cortex. For BIN1 rs744373, the association was observed only in minor allele carriers. For CD2AP rs9349407 and CR1 rs3818361, the association was preserved only in minor allele noncarriers. We did not find evidence for modulation by CLU, PICALM, ABCA7, BIN1, and MS4A6A. CONCLUSIONS: Our data show that BIN1 rs744373, CD2AP rs9349407, and CR1 rs3818361 genotypes modulate the association between apoE protein plasma levels and brain amyloidosis, implying a potential epigenetic/downstream interaction.

Low plasma ApoE levels are associated with smaller hippocampal size in the Alzheimer's disease neuroimaging initiative cohort.

Apolipoprotein E (APOE) genotype is the strongest known genetic risk factor for sporadic Alzheimer's disease (AD), but the utility of plasma ApoE levels for assessing the severity of underlying neurodegenerative changes remains uncertain. Here, we examined cross-sectional associations between plasma ApoE levels and volumetric magnetic resonance imaging indices of the hippocampus from 541 participants [57 with normal cognition (NC), 375 with mild cognitive impairment (MCI), and 109 with mild AD] who were enrolled in the Alzheimer's Disease Neuroimaging Initiative. Across the NC and MCI groups, lower plasma ApoE levels were significantly correlated with smaller hippocampal size, as measured by either hippocampal volume or hippocampal radial distance. These associations were driven primarily by findings from carriers of an APOE ε4 allele and are consistent with prior reports that lower plasma ApoE levels correlate with greater global cortical Pittsburgh Compound B retention. In this high-risk group, plasma ApoE levels may represent a peripheral marker of underlying AD neuropathology in nondemented elderly individuals.

ApoE4 effects on automated diagnostic classifiers for mild cognitive impairment and Alzheimer's disease.

Biomarkers are the only feasible way to detect and monitor presymptomatic Alzheimer's disease (AD). No single biomarker can predict future cognitive decline with an acceptable level of accuracy. In addition to designing powerful multimodal diagnostic platforms, a careful investigation of the major sources of disease heterogeneity and their influence on biomarker changes is needed. Here we investigated the accuracy of a novel multimodal biomarker classifier for differentiating cognitively normal (NC), mild cognitive impairment (MCI) and AD subjects with and without stratification by ApoE4 genotype. 111 NC, 182 MCI and 95 AD ADNI participants provided both structural MRI and CSF data at baseline. We used an automated machine-learning classifier to test the ability of hippocampal volume and CSF Aß, t-tau and p-tau levels, both separately and in combination, to differentiate NC, MCI and AD subjects, and predict conversion. We hypothesized that the combined hippocampal/CSF biomarker classifier model would achieve the highest accuracy in differentiating between the three diagnostic groups and that ApoE4 genotype will affect both diagnostic accuracy and biomarker selection. The combined hippocampal/CSF classifier performed better than hippocampus-only classifier in differentiating NC from MCI and NC from AD. It also outperformed the CSF-only classifier in differentiating NC vs. AD. Our amyloid marker played a role in discriminating NC from MCI or AD but not for MCI vs. AD. Neurodegenerative markers contributed to accurate discrimination of AD from NC and MCI but not NC from MCI. Classifiers predicting MCI conversion performed well only after ApoE4 stratification. Hippocampal volume and sex achieved AUC = 0.68 for predicting conversion in the ApoE4-positive MCI, while CSF p-tau, education and sex achieved AUC = 0.89 for predicting conversion in ApoE4-negative MCI. These observations support the proposed biomarker trajectory in AD, which postulates that amyloid markers become abnormal early in the disease course while markers of neurodegeneration become abnormal later in the disease course and suggests that ApoE4 could be at least partially responsible for some of the observed disease heterogeneity.

Mapping cortical atrophy in Parkinson's disease patients with dementia.

BACKGROUND: Cognitive impairment is very common in patients with Parkinson's disease (PD). Brain changes accompanying cognitive decline in PD are still not fully established. METHODS: We applied cortical pattern matching and cortical thickness analyses to the three-dimensional T1-weighted brain MRI scans of 14 age-matched cognitively normal elderly (NC), 12 cognitively normal PD (PDC), and 11 PD dementia (PDD) subjects. We used linear regression models to investigate the effect of diagnosis on cortical thickness. All maps were adjusted for multiple comparisons using permutation testing with a threshold p < 0.01. RESULTS: PDD showed significantly thinner bilateral sensorimotor, perisylvian, lateral parietal, as well as right posterior cingulate, parieto-occipital, inferior temporal and lateral frontal cortices relative to NC (left p(corrected) = 0.06, right p(corrected) = 0.009). PDD showed significantly thinner bilateral sensorimotor, right frontal and right parietal-occipital cortices relative to PDC (right p(corrected) = 0.05). The absolute difference in cortical thickness between PDD and the other diagnostic groups ranged from 3% to 19%. CONCLUSION: Our data shows that cognitive decline in PD is associated with cortical atrophy. PDD subjects have the most widespread gray matter atrophy suggesting more cortical involvement as PD patients progress to dementia.