Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
INTEGRA BIOSCIENCES AG

Download Mobile App




DNA Recombination in Brain Linked to Alzheimer's Disease

By LabMedica International staff writers
Posted on 05 Dec 2018
Alzheimer's disease is a public health crisis. More...
The cause of the disease remains unknown and no meaningful treatment exists. Nearly six million people in the USA are living with Alzheimer's disease, a number projected to reach 14 million by 2060 as the population ages.

The amyloid hypothesis, or the theory that accumulation of a protein called beta-amyloid in the brain causes Alzheimer's disease, has driven Alzheimer's studies to date. However, treatments that target beta-amyloid have notoriously failed in clinical trials.

A team of scientists associated with the Sanford Burnham Prebys Medical Discovery Institute (La Jolla, CA, USA) have identified gene recombination in neurons that produces thousands of new gene variants within Alzheimer's disease brains. The study reveals for the first time how the Alzheimer's-linked gene, Amyloid Beta Precursor Protein (APP), is recombined by using the same type of enzyme found in human immunodeficiency virus (HIV).

The investigators used new analytical methods that focused on single and multiple-cell samples, and found that the APP gene, which produces the toxic beta amyloid proteins defining Alzheimer's disease, gives rise to novel gene variants in neurons, creating a genomic mosaic. The process required reverse transcription and reinsertion of the variants back into the original genome, producing permanent DNA sequence changes within the cell's DNA blueprint.

All of the Alzheimer's disease brain samples contained an over-abundance of distinct APP gene variants, compared to samples from normal brains. The team discovered that neurons from the patients with Alzheimer’s disease contained about six times as many varieties of the APP gene as did the cells from the healthy people. Among these Alzheimer's-enriched variations, the scientists identified 11 single-nucleotide changes identical to known mutations in familial Alzheimer's disease, a very rare inherited form of the disorder. Although found in a mosaic pattern, the identical APP variants were observed in the most common form of Alzheimer's disease, further linking gene recombination in neurons to disease.

Jerold Chun, MD, PhD, a professor and senior author of the study said, “These findings may fundamentally change how we understand the brain and Alzheimer's disease. If we imagine DNA as a language that each cell uses to 'speak,' we found that in neurons, just a single word may produce many thousands of new, previously unrecognized words. This is a bit like a secret code embedded within our normal language that is decoded by gene recombination. The secret code is being used in healthy brains but also appears to be disrupted in Alzheimer's disease.” The study was published on November 21, 2018, in the journal Nature.

Related Links:
Sanford Burnham Prebys Medical Discovery Institute


Platinum Member
Automated Coagulation Analyzer
Hemolumi H6
Gold Member
Clinical Chemistry Assay
Sorbitol Dehydrogenase (SDH)
All-in-One Molecular System
AIO M160
New
Neurofilament Light Chain Assay
Lumipulse G NfL Blood
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Clinical Chemistry

view channel
Image: GRAIL’s Galleri test uses machine learning to analyze cfDNA patterns for cancer signals and predict their likely location to guide further evaluation.

Multi-Cancer Blood Test Expands Detection to Cancers Lacking Routine Screening Options

Many lethal cancers lack routine screening and are often diagnosed only after symptoms emerge, limiting curative options. Standard programs in the United States cover a small subset of malignancies, leaving... Read more

Immunology

view channel
Image: Although many people harbor latent Epstein-Barr virus (EBV), growing evidence has linked the virus to MS pathobiology (Image Credit: Adobe Stock)

Blood EBV Activity Biomarkers May Predict Multiple Sclerosis Relapse Months Ahead

Predicting relapse in multiple sclerosis (MS) remains difficult, limiting opportunities for timely intervention and monitoring. Although many people harbor latent Epstein-Barr virus (EBV), growing evidence... Read more

Microbiology

view channel
Image: Type 1 diabetes affects more than 9 million people worldwide and can begin years before symptoms appear, making early identification of at-risk children difficult (Image Credit: iStock)

Early-Life Gut Microbiome Changes May Help Assess Type 1 Diabetes Risk

Type 1 diabetes (T1D) affects more than 9 million people worldwide, including 1.8 million children and adolescents, and often begins years before symptoms appear. Early identification of children who are... Read more

Pathology

view channel
Image: A new study demonstrates that vascular features in colorectal tumors could serve as prognostic biomarkers of disease outcome. (Image Credit: iStock)

Tumor Blood Vessel Features May Help Predict Colorectal Cancer Survival

Colorectal cancer outcomes vary widely, and tumor biology remains a key determinant of prognosis. Because neoplasms depend on a vascular supply, differences in intratumoral vessels may influence survival.... Read more

Technology

view channel
Image: ADLM recommends that emerging AI tools follow the same professional oversight, quality, validation, and monitoring standards as traditional clinical testing within CLIA’s existing framework (Image Credit: Adobe Stock)

ADLM Calls for CLIA Updates to Support Safe AI Use in Laboratory Medicine

Clinical laboratories increasingly use artificial intelligence to verify, interpret, and report results, but safeguards under the Clinical Laboratory Improvement Amendments (CLIA) were designed in 1992.... Read more

Industry

view channel
Image: Central to the collaboration is the Enhanced Liver Fibrosis (ELF) test, a noninvasive blood test authorized in the U.S. to assess disease progression risk in patients with advanced fibrosis due to MASH and support patient management decisions. (Photo courtesy of Siemens Healthineers)

Siemens Healthineers and Novo Collaborate to Expand Access to Noninvasive Liver Testing

Metabolic dysfunction‑associated steatotic liver disease (MASLD) and its progressive form, metabolic dysfunction‑associated steatohepatitis (MASH), affect millions and are linked to obesity, type 2 diabetes,... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.