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.

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.

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.

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.

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.

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 Aβ, 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.

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 β-amyloid 1-42 (Aβ42) ≤ 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 Aβ42 but no PiB-PET data and tested its performance in the subcohort with PiB-PET but no CSF Aβ42 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%).

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.