The early-onset Alzheimer's disease MRI signature: a replication and extension analysis in early-stage AD.

Early-onset Alzheimer's disease (EOAD) is less investigated than the more common late-onset Alzheimer's disease (LOAD) despite its more aggressive course. A cortical signature of EOAD was recently proposed and may facilitate EOAD investigation. Here, we aimed to validate this proposed MRI biomarker of EOAD neurodegeneration in an Appalachian clinical cohort.

Memory consolidation, temporal and parietal atrophy, and metabolism in amyloid-β positive and negative mild cognitive impairment.

Background: Alzheimer's disease (AD) is classically characterized by alterations in memory consolidation. With the advent of diagnostic biomarkers, some patients clinically diagnosed with AD display biomarkers inconsistent with the diagnosis.

Objective: We aimed to explore differences in memory consolidation and neurodegeneration of the temporal and parietal lobes as a function of amyloid-β status in amnestic mild cognitive impairment (aMCI).

Executive function and cortical thickness in biomarker aMCI.

Introduction: Memory deficits are the primary symptom in amnestic Mild Cognitive Impairment (aMCI); however, executive function (EF) deficits are common. The current study examined EF in aMCI based upon amyloid status (A+/A-) and regional atrophy in signature areas of Alzheimer's disease (AD).

Method: Participants included 110 individuals with aMCI (A+ = 66; A- = 44) and 33 cognitively healthy participants (HP).

Cortical Thickness Correlates of Go/No-go and Motor Sequencing in Mild Cognitive Impairment and Suspected Alzheimer Disease Dementia.

Background: While the cognitive hallmark of typical Alzheimer disease (AD) is impaired memory consolidation, increasing evidence suggests that the frontal lobes and associated executive functions are also impacted.

Objective: We examined two neurobehavioral executive function tasks and associations with cortical thickness in patients diagnosed with mild cognitive impairment (MCI), suspected AD dementia, and a healthy control group.

Methods: First, we compared group performances on a go/no-go (GNG) task and on Luria's Fist-Edge-Palm (FEP) motor sequencing task.

More Similar than Different: Memory, Executive Functions, Cortical Thickness, and Glucose Metabolism in Biomarker-Positive Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia.

Background: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are typically associated with very different clinical and neuroanatomical presentations; however, there is increasing recognition of similarities.

Objective: To examine memory and executive functions, as well as cortical thickness, and glucose metabolism in AD and bvFTD signature brain regions.

Methods: We compared differences in a group of biomarker-defined participants with Alzheimer's disease and a group of clinically diagnosed participants with bvFTD.

Ultrasound Blood-Brain Barrier Opening and Aducanumab in Alzheimer's Disease.

Antiamyloid antibodies have been used to reduce cerebral amyloid-beta (Aβ) load in patients with Alzheimer's disease. We applied focused ultrasound with each of six monthly aducanumab infusions to temporarily open the blood-brain barrier with the goal of enhancing amyloid removal in selected brain regions in three participants over a period of 6 months. The reduction in the level of Aβ was numerically greater in regions treated with focused ultrasound than in the homologous regions in the contralateral hemisphere that were not treated with focused ultrasound, as measured by fluorine-18 florbetaben positron-emission tomography.

Developing, implementing, and evaluating the visiting Neighbors' program in rural Appalachia: A quality improvement protocol.

Introduction: Older adults living alone in rural areas frequently experience health declines, social isolation, and limited access to services. To address these challenges, our medical academic university supported a quality improvement project for developing and evaluating the Visiting Neighbors program in two rural Appalachian counties. Our Visiting Neighbors program trained local volunteers to visit and guide rural older adults in healthy activities.

Surface-based correlates of cognition along the Alzheimer's continuum in a memory clinic population.

Composite cognitive measures in large-scale studies with biomarker data for amyloid and tau have been widely used to characterize Alzheimer's disease (AD). However, little is known about how the findings from these studies translate to memory clinic populations without biomarker data, using single measures of cognition. Additionally, most studies have utilized voxel-based morphometry or limited surface-based morphometry such as cortical thickness, to measure the neurodegeneration associated with cognitive deficits.

Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations.

Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent.

Association of Predicted Expression and Multimodel Association Analysis of Substance Abuse Traits.

Introduction: Genome-wide association studies (GWAS) have played a critical role in identifying many thousands of loci associated with complex phenotypes and diseases. This has led to several translations of novel disease susceptibility genes into drug targets and care. This however has not been the case for analyses where sample sizes are small, which suffer from multiple comparisons testing.

Frontal and temporal lobe correlates of verbal learning and memory in aMCI and suspected Alzheimer's disease dementia.

Alzheimer's disease is primarily known for deficits in learning and retaining new information. This has long been associated with pathological changes in the mesial temporal lobes. The role of the frontal lobes in memory in Alzheimer's disease is less well understood.

Focused ultrasound-mediated blood-brain barrier opening in Alzheimer's disease: long-term safety, imaging, and cognitive outcomes.

Objective: MRI-guided low-intensity focused ultrasound (FUS) has been shown to reversibly open the blood-brain barrier (BBB), with the potential to deliver therapeutic agents noninvasively to target brain regions in patients with Alzheimer's disease (AD) and other neurodegenerative conditions. Previously, the authors reported the short-term safety and feasibility of FUS BBB opening of the hippocampus and entorhinal cortex (EC) in patients with AD. Given the need to treat larger brain regions beyond the hippocampus and EC, brain volumes and locations treated with FUS have now expanded.

Procedural learning and retention relative to explicit learning and retention in mild cognitive impairment and Alzheimer's disease using a modification of the trail making test.

Amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) dementia are characterized by pathological changes to the medial temporal lobes, resulting in explicit learning and retention reductions. Studies demonstrate that implicit/procedural memory processes are relatively intact in these populations, supporting different anatomical substrates for differing memory systems. This study examined differences between explicit and procedural learning and retention in individuals with aMCI and AD dementia relative to matched healthy controls.

A greedy regression algorithm with coarse weights offers novel advantages.

Regularized regression analysis is a mature analytic approach to identify weighted sums of variables predicting outcomes. We present a novel Coarse Approximation Linear Function (CALF) to frugally select important predictors and build simple but powerful predictive models. CALF is a linear regression strategy applied to normalized data that uses nonzero weights + 1 or - 1.

TWO-SIGMA-G: a new competitive gene set testing framework for scRNA-seq data accounting for inter-gene and cell-cell correlation.

We propose TWO-SIGMA-G, a competitive gene set test for scRNA-seq data. TWO-SIGMA-G uses a mixed-effects regression model based on our previously published TWO-SIGMA to test for differential expression at the gene-level. This regression-based model provides flexibility and rigor at the gene-level in (1) handling complex experimental designs, (2) accounting for the correlation between biological replicates and (3) accommodating the distribution of scRNA-seq data to improve statistical inference.

Effects of genetic risk for alcohol dependence and onset of regular drinking on the progression to alcohol dependence: A polygenic risk score approach.

Background: Prior studies have established the importance of genetic contributions to the etiology of alcohol dependence (AD), and suggested an early onset of alcohol use represents an initial marker of this genetic risk, which is associated with a more rapid progression to AD and increased risk for AD itself. Building on prior work, the current study examined whether the additive effects of AD risk variants predicted the rate of progression to AD from the onset of regular drinking, a drinking milestone with high clinical relevance to AD prevention.

Methods: Data from 1501 European-ancestry adults from the University of California - San Francisco Family Alcoholism Study were used to examine whether polygenic risk scores for AD (PRS) and age-at-onset of regular drinking contributed uniquely to the likelihood of having a lifetime AD diagnosis and the rate of progression from regular drinking to AD.

Pre-capture multiplexing provides additional power to detect copy number variation in exome sequencing.

Background: As exome sequencing (ES) integrates into clinical practice, we should make every effort to utilize all information generated. Copy-number variation can lead to Mendelian disorders, but small copy-number variants (CNVs) often get overlooked or obscured by under-powered data collection. Many groups have developed methodology for detecting CNVs from ES, but existing methods often perform poorly for small CNVs and rely on large numbers of samples not always available to clinical laboratories.

Noninvasive prenatal exome sequencing diagnostic utility limited by sequencing depth and fetal fraction.

Objective: Sequencing cell-free DNA now allows detection of large chromosomal abnormalities and dominant Mendelian disorders in the prenatal period. Improving upon these methods would allow newborn screening programs to begin with prenatal genetics, ultimately improving the management of rare genetic disorders.

Methods: As a pilot study, we performed exome sequencing on the cell-free DNA from three mothers with singleton pregnancies to assess the viability of broad sequencing modalities in a noninvasive prenatal setting.

Cryptic developmental events determine medulloblastoma radiosensitivity and cellular heterogeneity without altering transcriptomic profile.

It is unclear why medulloblastoma patients receiving similar treatments experience different outcomes. Transcriptomic profiling identified subgroups with different prognoses, but in each subgroup, individuals remain at risk of incurable recurrence. To investigate why similar-appearing tumors produce variable outcomes, we analyzed medulloblastomas triggered in transgenic mice by a common driver mutation expressed at different points in brain development.

SMNN: batch effect correction for single-cell RNA-seq data via supervised mutual nearest neighbor detection.

Batch effect correction has been recognized to be indispensable when integrating single-cell RNA sequencing (scRNA-seq) data from multiple batches. State-of-the-art methods ignore single-cell cluster label information, but such information can improve the effectiveness of batch effect correction, particularly under realistic scenarios where biological differences are not orthogonal to batch effects. To address this issue, we propose SMNN for batch effect correction of scRNA-seq data via supervised mutual nearest neighbor detection.