MiR-107 is Reduced in Alzheimer\u27s Disease Brain Neocortex: Validation Study

MiR-107 is a microRNA (miRNA) that we reported previously to have decreased expression in the temporal cortical gray matter early in the progression of Alzheimer\u27s disease (AD). Here we study a new group of well-characterized human temporal cortex samples (N=19). MiR-107 expression was assessed, normalized to miR-124 and let-7a. Correlation was observed between decreased miR-107 expression and increased neuritic plaque counts (P\u3c 0.05) and neurofibrillary tangle counts (P\u3c 0.02) in adjacent brain tissue. Adjusted miR-107 and BACE1 mRNA levels tended to correlate negatively (trend with regression P\u3c 0.07). In sum, miR-107 expression tends to be lower relative to other miRNAs as AD progresses

Hippocampal Sclerosis of Aging, a Common Alzheimer's Disease 'Mimic': Risk Genotypes are Associated with Brain Atrophy Outside the Temporal Lobe

Hippocampal sclerosis of aging (HS-Aging) is a common brain disease in older adults with a clinical course that is similar to Alzheimer's disease. Four single-nucleotide polymorphisms (SNPs) have previously shown association with HS-Aging. The present study investigated structural brain changes associated with these SNPs using surface-based analysis. Participants from the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; n = 1,239), with both MRI scans and genotype data, were used to assess the association between brain atrophy and previously identified HS-Aging risk SNPs in the following genes: GRN, TMEM106B, ABCC9, and KCNMB2 (minor allele frequency for each is >30%). A fifth SNP (near the ABCC9 gene) was evaluated in post-hoc analysis. The GRN risk SNP (rs5848_T) was associated with a pattern of atrophy in the dorsomedial frontal lobes bilaterally, remarkable since GRN is a risk factor for frontotemporal dementia. The ABCC9 risk SNP (rs704180_A) was associated with multifocal atrophy whereas a SNP (rs7488080_A) nearby (∼50 kb upstream) ABCC9 was associated with atrophy in the right entorhinal cortex. Neither TMEM106B (rs1990622_T), KCNMB2 (rs9637454_A), nor any of the non-risk alleles were associated with brain atrophy. When all four previously identified HS-Aging risk SNPs were summed into a polygenic risk score, there was a pattern of associated multifocal brain atrophy in a predominately frontal pattern. We conclude that common SNPs previously linked to HS-Aging pathology were associated with a distinct pattern of anterior cortical atrophy. Genetic variation associated with HS-Aging pathology may represent a non-Alzheimer's disease contribution to atrophy outside of the hippocampus in older adults

Circulating MicroRNAs in Alzheimer\u27s Disease: The Search for Novel Biomarkers

Alzheimer\u27s disease (AD) is the most common neurodegenerative disease in the elderly. While advancements have been made in understanding the genetic and molecular basis of AD, the clinical diagnosis of AD remains difficult, and post-mortem confirmation is often required. Furthermore, the onset of neurodegeneration precedes clinical symptoms by approximately a decade. Consequently, there is a crucial need for an early and accurate diagnosis of AD, which can potentially lead to strategies that can slow down or stop the progression of neurodegeneration and dementia. Recent advances in the non-coding RNA field have shown that microRNAs (miRNAs) can function as powerful biomarkers in human diseases. Studies are emerging suggesting that circulating miRNAs in the cerebrospinal fluid and blood serum have characteristic changes in AD patients. Whether miRNAs can be used in AD diagnosis, alone or in combination with other AD biomarkers (e.g., amyloid and tau), warrants further investigation

Quantitative Neuropathological Assessment to Investigate Cerebral Multi-Morbidity

The aging brain is characterized by the simultaneous presence of multiple pathologies, and the prevalence of cerebral multi-morbidity increases with age. To understand the impact of each subtype of pathology and the combined effects of cerebral multi-morbidity on clinical signs and symptoms, large clinico-pathological correlative studies have been performed. However, such studies are often based on semi-quantitative assessment of neuropathological hallmark lesions. Here, we discuss some of the new methods for high-throughput quantitative neuropathological assessment. These methods combine increased quantitative rigor with the added technical capacity of computers and networked analyses. There are abundant new opportunities - with specific techniques that include slide scanners, automated microscopes, and tissue microarrays - and also potential pitfalls. We conclude that quantitative and digital neuropathologic approaches will be key resources to further elucidate cerebral multi-morbidity in the aged brain and also hold the potential for changing routine neuropathologic diagnoses

Circulating MicroRNAs in Alzheimer\u27s Disease: The Search for Novel Biomarkers

Alzheimer\u27s disease (AD) is the most common neurodegenerative disease in the elderly. While advancements have been made in understanding the genetic and molecular basis of AD, the clinical diagnosis of AD remains difficult, and post-mortem confirmation is often required. Furthermore, the onset of neurodegeneration precedes clinical symptoms by approximately a decade. Consequently, there is a crucial need for an early and accurate diagnosis of AD, which can potentially lead to strategies that can slow down or stop the progression of neurodegeneration and dementia. Recent advances in the non-coding RNA field have shown that microRNAs (miRNAs) can function as powerful biomarkers in human diseases. Studies are emerging suggesting that circulating miRNAs in the cerebrospinal fluid and blood serum have characteristic changes in AD patients. Whether miRNAs can be used in AD diagnosis, alone or in combination with other AD biomarkers (e.g., amyloid and tau), warrants further investigation

MicroRNA in Situ Hybridization in the Human Entorhinal and Transentorhinal Cortex

MicroRNAs (miRNAs) play key roles in gene expression regulation in both healthy and disease brains. To better understand those roles, it is necessary to characterize the miRNAs that are expressed in particular cell types under a range of conditions. In situ hybridization (ISH) can demonstrate cell- and lamina-specific patterns of miRNA expression that would be lost in tissue-level expression profiling. In the present study, ISH was performed with special focus on the human entorhinal cortex (EC) and transentorhinal cortex (TEC). The TEC is the area of the cerebral cortex that first develops neurofibrillary tangles in Alzheimer\u27s disease (AD). However, the reason for TEC\u27s special vulnerability to AD-type pathology is unknown. MiRNA ISH was performed on three human brains with well-characterized clinical and pathological parameters. Locked nucleic acid ISH probes were used referent to miR-107, miR-124, miR-125b, and miR-320. In order to correlate the ISH data with AD pathology, the ISH staining was compared with near-adjacent slides processed using Thioflavine stains. Not all neurons or cortical lamina stain with equal intensity for individual miRNAs. As with other areas of brain, the TEC and EC have characteristic miRNA expression patterns. MiRNA ISH is among the first methods to show special staining characteristics of cells and laminae of the human TEC

Glimepiride Administered in Chow Reversibly Impairs Glucose Tolerance in Mice

Sulfonylureas are a class of antidiabetes medications prescribed to millions of individuals worldwide. Rodents have been used extensively to study sulfonylureas in the laboratory. Here, we report the results of studies treating mice with a sulfonylurea (glimepiride) in order to understand how the drug affects glucose homeostasis and tolerance. We tested the effect of glimepiride on fasting blood glucose, glucose tolerance, and insulin secretion, using glimepiride sourced from a local pharmacy. We also examined the effect on glucagon, gluconeogenesis, and insulin sensitivity. Unexpectedly, glimepiride exposure in mice was associated with fasting hyperglycemia, glucose intolerance, and decreased insulin. There was no change in circulating glucagon levels or gluconeogenesis. The effect was dose-dependent, took effect by two weeks, and was reversed within three weeks after removal. Glimepiride elicited the same effects in all strains evaluated: four wild-type strains, as well as the transgenic Grn−/− and diabetic db/db mice. Our findings suggest that the use of glimepiride as a hypoglycemic agent in mice should proceed with caution and may have broader implications about mouse models as a proxy to study the human pharmacopeia

Random Forest-Integrated Analysis in AD and LATE Brain Transcriptome-Wide Data to Identify Disease-Specific Gene Expression

Alzheimer\u27s disease (AD) is a complex neurodegenerative disorder that affects thinking, memory, and behavior. Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a recently identified common neurodegenerative disease that mimics the clinical symptoms of AD. The development of drugs to prevent or treat these neurodegenerative diseases has been slow, partly because the genes associated with these diseases are incompletely understood. A notable hindrance from data analysis perspective is that, usually, the clinical samples for patients and controls are highly imbalanced, thus rendering it challenging to apply most existing machine learning algorithms to directly analyze such datasets. Meeting this data analysis challenge is critical, as more specific disease-associated gene identification may enable new insights into underlying disease-driving mechanisms and help find biomarkers and, in turn, improve prospects for effective treatment strategies. In order to detect disease-associated genes based on imbalanced transcriptome-wide data, we proposed an integrated multiple random forests (IMRF) algorithm. IMRF is effective in differentiating putative genes associated with subjects having LATE and/or AD from controls based on transcriptome-wide data, thereby enabling effective discrimination between these samples. Various forms of validations, such as cross-domain verification of our method over other datasets, improved and competitive classification performance by using identified genes, effectiveness of testing data with a classifier that is completely independent from decision trees and random forests, and relationships with prior AD and LATE studies on the genes linked to neurodegeneration, all testify to the effectiveness of IMRF in identifying genes with altered expression in LATE and/or AD. We conclude that IMRF, as an effective feature selection algorithm for imbalanced data, is promising to facilitate the development of new gene biomarkers as well as targets for effective strategies of disease prevention and treatment

MicroRNAs (miRNAs) in Neurodegenerative Diseases

Aging-related neurodegenerative diseases (NDs) are the culmination of many different genetic and environmental influences. Prior studies have shown that RNAs are pathologically altered during the inexorable course of some NDs. Recent evidence suggests that microRNAs (miRNAs) may be a contributing factor in neurodegeneration. miRNAs are brain-enriched, small (~22 nucleotides) non-coding RNAs that participate in mRNA translational regulation. Although discovered in the framework of worm development, miRNAs are now appreciated to play a dynamic role in many mammalian brain-related biochemical pathways, including neuroplasticity and stress responses. Research about miRNAs in the context of neurodegeneration is accumulating rapidly, and the goal of this review is to provide perspective for these new data that may be helpful to specialists in either field. An overview is provided about the normal functions for miRNAs, including some of the newer concepts related to the human brain. Recently published studies pertaining to the roles of miRNAs in NDs––including Alzheimer’s disease, Parkinson’s disease and triplet repeat disorders—are described. Finally, a discussion is included with theoretical syntheses and possible future directions in exploring the nexus between miRNA and ND research