Alzheimer's disease brain: alterations in RNA levels and in a ribonuclease-inhibitor complex

Science ◽  
1984 ◽  
Vol 225 (4665) ◽  
pp. 947-949 ◽  
Author(s):  
E. Sajdel-Sulkowska ◽  
C. Marotta
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Ribonuclease Inhibitor ◽  
Inhibitor Complex ◽  
Rna Levels

scholarly journals Lithium alters expression of RNAs in a type-specific manner in differentiated human neuroblastoma neuronal cultures, including specific genes involved in Alzheimer’s disease

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bryan Maloney ◽  
Yokesh Balaraman ◽  
Yunlong Liu ◽  
Nipun Chopra ◽  
Howard J. Edenberg ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Bipolar Disorders ◽  
Sequence Length ◽  
Neuronal Cultures ◽  
Human Neuroblastoma ◽  
Protein Coding ◽  
Whole Transcriptome ◽  
Nucleolar Rnas ◽  
Rna Levels

AbstractLithium (Li) is a medication long-used to treat bipolar disorder. It is currently under investigation for multiple nervous system disorders, including Alzheimer’s disease (AD). While perturbation of RNA levels by Li has been previously reported, its effects on the whole transcriptome has been given little attention. We, therefore, sought to determine comprehensive effects of Li treatment on RNA levels. We cultured and differentiated human neuroblastoma (SK-N-SH) cells to neuronal cells with all-trans retinoic acid (ATRA). We exposed cultures for one week to lithium chloride or distilled water, extracted total RNA, depleted ribosomal RNA and performed whole-transcriptome RT-sequencing. We analyzed results by RNA length and type. We further analyzed expression and protein interaction networks between selected Li-altered protein-coding RNAs and common AD-associated gene products. Lithium changed expression of RNAs in both non-specific (inverse to sequence length) and specific (according to RNA type) fashions. The non-coding small nucleolar RNAs (snoRNAs) were subject to the greatest length-adjusted Li influence. When RNA length effects were taken into account, microRNAs as a group were significantly less likely to have had levels altered by Li treatment. Notably, several Li-influenced protein-coding RNAs were co-expressed or produced proteins that interacted with several common AD-associated genes and proteins. Lithium’s modification of RNA levels depends on both RNA length and type. Li activity on snoRNA levels may pertain to bipolar disorders while Li modification of protein coding RNAs may be relevant to AD.

scholarly journals Predicting Clinical Dementia Rating Using Blood RNA Levels

2019 ◽  
Author(s):  
Justin B. Miller ◽  
John S.K. Kauwe ◽  
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Microarray Data ◽  
Predictive Accuracy ◽  
Cognitive Status ◽  
Clinical Dementia Rating ◽  
P Values ◽  
Intracellular Channel ◽  
Rna Levels

Structured AbstractINTRODUCTIONThe Clinical Dementia Rating (CDR) is commonly used to assess cognitive decline in Alzheimer’s disease patients.METHODSWe divided 741 participants with blood microarray data in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) into three groups based on their most recent CDR assessment: cognitive normal (CDR=0), mild dementia (CDR=0.5), and probable AD (CDR≥1.0). We then used machine learning to predict cognitive status using only blood RNA levels.RESULTSOne chloride intracellular channel 1 (CLIC1) probe was significant. By combining nonsignificant probes with p-values less than 0.1, we averaged 87.87 (s = 1.02)% predictive accuracy in classifying the three groups, compared to a 55.46% baseline for this study.DISCUSSIONWe identified one significant probe in CLIC1. However, CLIC1 levels alone were not sufficient to determine dementia status. We propose that combining individually suggestive, but nonsignificant, blood RNA levels can significantly improve diagnostic accuracy.

scholarly journals TOMM40 RNA Transcription in Alzheimer’s Disease Brain and Its Implication in Mitochondrial Dysfunction

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 871
Author(s):  
Eun-Gyung Lee ◽  
Sunny Chen ◽  
Lesley Leong ◽  
Jessica Tulloch ◽  
Chang-En Yu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mitochondrial Dysfunction ◽  
Postmortem Brain ◽  
Human Postmortem Brain ◽  
Mitochondrial Dna Copy Number ◽  
Mitochondrial Functions ◽  
Differential Transcription ◽  
And Control ◽  
Rna Levels

Increasing evidence suggests that the Translocase of Outer Mitochondria Membrane 40 (TOMM40) gene may contribute to the risk of Alzheimer’s disease (AD). Currently, there is no consensus as to whether TOMM40 expression is up- or down-regulated in AD brains, hindering a clear interpretation of TOMM40’s role in this disease. The aim of this study was to determine if TOMM40 RNA levels differ between AD and control brains. We applied RT-qPCR to study TOMM40 transcription in human postmortem brain (PMB) and assessed associations of these RNA levels with genetic variants in APOE and TOMM40. We also compared TOMM40 RNA levels with mitochondrial functions in human cell lines. Initially, we found that the human genome carries multiple TOMM40 pseudogenes capable of producing highly homologous RNAs that can obscure precise TOMM40 RNA measurements. To circumvent this obstacle, we developed a novel RNA expression assay targeting the primary transcript of TOMM40. Using this assay, we showed that TOMM40 RNA was upregulated in AD PMB. Additionally, elevated TOMM40 RNA levels were associated with decreases in mitochondrial DNA copy number and mitochondrial membrane potential in oxidative stress-challenged cells. Overall, differential transcription of TOMM40 RNA in the brain is associated with AD and could be an indicator of mitochondrial dysfunction.

Brain messenger RNA levels and ribonuclease activity in Alzheimer's disease

1987 ◽  
Vol 15 (1) ◽  
pp. 133-134 ◽  
Author(s):  
M. R. MORRISON ◽  
S. PARDUE ◽  
K. MASCHOFF ◽  
W. S. T. GRIFFIN ◽  
C. L. WHITE ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Messenger Rna ◽  
Ribonuclease Activity ◽  
Rna Levels

scholarly journals Predicting Clinical Dementia Rating Using Blood RNA Levels

Genes ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 706
Author(s):  
Justin B. Miller ◽  
John S. K. Kauwe
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Cognitive Status ◽  
Clinical Dementia Rating ◽  
Intracellular Channel ◽  
Rna Levels

The Clinical Dementia Rating (CDR) is commonly used to assess cognitive decline in Alzheimer’s disease patients and is included in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. We divided 741 ADNI participants with blood microarray data into three groups based on their most recent CDR assessment: cognitive normal (CDR = 0), mild cognitive impairment (CDR = 0.5), and probable Alzheimer’s disease (CDR ≥ 1.0). We then used machine learning to predict cognitive status using only blood RNA levels. Only one probe for chloride intracellular channel 1 (CLIC1) was significant after correction. However, by combining individually nonsignificant probes with p-values less than 0.1, we averaged 87.87% (s = 1.02) predictive accuracy for classifying the three groups, compared to a 55.46% baseline for this study due to unequal group sizes. The best model had an overall precision of 0.902, recall of 0.895, and a receiver operating characteristic (ROC) curve area of 0.904. Although we identified one significant probe in CLIC1, CLIC1 levels alone were not sufficient to predict dementia status and cannot be used alone in a clinical setting. Additional analyses combining individually suggestive, but nonsignificant, blood RNA levels were significantly predictive and may improve diagnostic accuracy for Alzheimer’s disease. Therefore, we propose that patient features that do not individually predict cognitive status might still contribute to overall cognitive decline through interactions that can be elucidated through machine learning.

Cognitive control constrains memory attributions

2019 ◽  
Vol 42 ◽  
Author(s):  
Colleen M. Kelley ◽  
Larry L. Jacoby
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Cognitive Control

Abstract Cognitive control constrains retrieval processing and so restricts what comes to mind as input to the attribution system. We review evidence that older adults, patients with Alzheimer's disease, and people with traumatic brain injury exert less cognitive control during retrieval, and so are susceptible to memory misattributions in the form of dramatic levels of false remembering.

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