Methods for assessing neuroinflammation using somatic mutations in Alzheimer's Disease

Background

Alzheimer’s disease (AD) is a neurodegenerative condition that affects about 1 in 9 Americans aged 65 and older, with almost 7 million people currently affected and 14 million expected to be affected by 2060. One of the early pathogenic processes in AD is neuroinflammation, which generally starts long before symptoms occur.  Somatic mutations, genomic variants that emerge post-zygote formation and accumulate during human development, have emerged as crucial factors contributing to various diseases and their role in neuroinflammation. These mutations play an important role in many disorders besides AD such as in autism, cortical malformation, as well as in some rare neurodegenerative diseases. With the advent of advanced next-generation sequencing technologies, it is possible to identify somatic mutations for the improved diagnosis and treatment of neurological disorders, however sophisticated methods are needed to distinguish these mutations accurately from a much larger number of germline mutations and technical artifacts.

Technology Overview

Boston Children’s Hospital has pioneered a groundbreaking computational algorithm designed for the identification of somatic mutations. Leveraging two complementary sequencing technologies (deep panel sequencing with molecular barcoding) enables the detection of somatic mutations even at an allele fraction as low as 0.1%. The methods exhibit high sensitivity and low false positive rates in detecting somatic mutations and were demonstrated in studying the role of clonal somatic single-nucleotide variations in AD. Analyzing brain RNA-seq data from over 1,000 participants across two AD cohorts (ROSMAP and Mayo Clinic), the research consistently identified an elevated burden of somatic mutations in the AD prefrontal cortex (PFC) compared to age-matched control PFC. These findings underscore the possible contribution of clonally expanding glial cells, particularly microglia activated by somatic mutations, to AD pathogenesis. The implications extend to diagnostics and therapeutics, suggesting the screening of patients for somatic mosaic contributions through DNA or RNA sequencing of blood or cerebrospinal fluid. This identification can guide targeted therapies, especially using drugs that target proliferation-related pathways, which have proven effective in cancer treatment.

Applications

• Improved diagnosis and targeted treatment of Alzheimer’s disease and other disorders related somatic mutation such as certain cancers, autism spectrum disorder, and cortical malformations

Advantages

• Increased accuracy in distinguishing AD from other forms of dementia and neurodegenerative disease
• Early detection capabilities by identifying pathogenic processes before clinical symptoms manifest
• Currently, Alzheimer's disease lacks a cure, with treatments focused only on symptom relief that diminishes in efficacy over time. Targeting proliferation-related pathways, proven in cancer treatment, emerges as a potential therapeutic approach to suppress the somatic-mutation-activated microglia, ultimately mitigating the neurodegeneration in Alzheimer's disease. 

Publications

• Huang AY, Zhou Z, Talukdar M, Miller MB, Chhouk B, Enyenihi L, Rosen I, Stronge E, Zhao B, Kim D, Choi J, Khoshkhoo S, Kim J, Ganz J, Travaglini K, Gabitto M, Hodge R, Kaplan E, Lein E, De Jager PL, Bennett DA, Lee EA, Walsh CA. Somatic cancer driver mutations are enriched and associated with inflammatory states in Alzheimer's disease microglia. bioRxiv [Preprint]. 2024 Jan 4:2024.01.03.574078. doi: 10.1101/2024.01.03.574078. PMID: 38260600; PMCID: PMC10802273.