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US 2026/0308681 A1Published application
Compositions and methods for assessing neuroinflammation using somatic mutations
AssigneeChildren's Medical Center Corporation
InventorsYue Huang, Zinan Zhou, Eunjung A. Lee, Christopher A. Walsh
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Abstract
This disclosure relates generally to compositions and methods for assessing neuroinflammation based on the presence of absence of somatic mutations. The compositions and methods provided herein are useful for predicting a subject's risk of chronic neuroinflammation. In addition, this disclosure provides therapeutic agents that can be used to reduce or prevent neuroinflammation.
Claims20
A method of characterizing neuroinflammation in a biological sample of a subject, the method comprising:
- a) sequencing a set of proliferation-related or cell cycle-related polynucleotides to generate sequencing reads, wherein each polynucleotide comprises a unique molecular identifier (UMIs), and wherein the polynucleotides are derived from a biological sample of a subject comprising somatic cells;
- b) generating a consensus sequence for each group of sequencing reads comprising the same UMI;
- c) comparing the consensus sequence to a reference sequence to identify somatic single nucleotide variations (sSNVs) and somatic indels in the consensus sequence that are not present in the reference sequence, wherein the presence of sSNVs and somatic indels in the consensus sequence is indicative of neuroinflammation in the biological sample.
A computer implemented method of determining a burden of somatic mutations in a biological sample of a subject, the method comprising:
- a) sequencing RNA present in a biological sample comprising somatic cells of the subject to generate sequencing data;
- b) aligning a set of RNA sequences in the sequencing data against a human reference genome to obtain alignment reads;
- c) filtering the alignment reads to remove duplicate genomes, for indel realignment, for base quality recalibration to exclude improperly paired or ambiguous alignments, excluding A-to-I(G) RNA editing sites, such that only non-A-to-G RNA sequences undergo further analysis, and/or excluding non-exonic candidates and candidates that are present in the polymorphism databases of the general human population;
- thereby generating a set of non-A-to-G, autosomal, exonic, somatic mutations present in the sample;
- and
- d) calculating the burden of somatic mutations in the biological sample relative to the reference sequence.
3 more elements
A method of characterizing Alzheimer's disease in a biological sample of a subject, the method comprising:
- a) deep DNA panel sequencing a set of proliferation-related or cell cycle-related polynucleotides to generate sequencing reads, wherein each polynucleotide comprises a unique molecular identifier (UMIs), and wherein the polynucleotides are derived from a biological sample comprising somatic cells;
- b) generating a consensus sequence for each group of sequencing reads comprising the same UMI;
- c) comparing the consensus sequence to a reference sequence to identify somatic single nucleotide variations (sSNVs) and somatic indels in the consensus sequence that are not present in the reference sequence, wherein the presence of sSNVs and somatic indels in the consensus sequence relative to a reference is indicative of Alzheimer's disease or a propensity to develop Alzheimer's disease in the subject and the absence of sSNVs and somatic indels in the consensus sequence relative to a reference is indicative that the subject does not have Alzheimer's disease or a propensity to develop Alzheimer's disease;
- or
- a) sequencing RNA present in a biological sample comprising somatic cells of the subject to generate sequencing data;
- b) aligning a set of RNA sequences in the sequencing data against a human reference genome to obtain alignment reads;
- c) filtering the alignment reads to remove duplicate genomes, for indel realignment, for base quality recalibration to exclude improperly paired or ambiguous alignments, excluding A-to-I(G) RNA editing sites, such that only non-A-to-G RNA sequences undergo further analysis, and/or excluding non-exonic candidates and candidates that are present in the polymorphism databases of the general human population;
- thereby generating a set of non-A-to-G, autosomal, exonic, somatic mutations present in the sample;
- and
- d) calculating the burden of somatic mutations in the biological sample relative to the reference sequence, wherein an increase in the burden of somatic mutations is indicative that the subject has or has a propensity to develop Alzheimer's disease;
- or
- a) bulk sequencing RNA from a biological sample of a subject to identify somatic mutations in expressed genes;
- b) deep sequencing genomic DNA from a biological sample of the subject to identify somatic single-nucleotide variations in the genomic DNA;
- and
- c) determining the number of somatic single-nucleotide variations identified by bulk sequencing RNA and deep sequencing of genomic DNA relative to a reference, wherein increased somatic single-nucleotide variations in RNA and DNA relative to the reference indicates neuroinflammation or Alzheimer's disease.
12 more elements
A panel of capture molecules for detection of an sSNV, sIndel, or mutation burden in a gene selected from the group consisting of:
- AKT3, AKT1, ASXL1, ATRX BCR, CBL;
- CHEK2, CHK2, CX3CR1, DEPDC5;
- DNMT3A, EPPK1, KMT2D, MED12, MLH1, MS4A7 MRC1, MTOR, PDGFRA, PI3K, PIK3CA, PIK3R1, PPM1D, P2RY12, STAT3, TSC1, TET2, TMEM119, and TP53, wherein the capture molecule is a polynucleotide or polypeptide.
A method of reducing neuroinflammation in a subject, the method comprising contacting a cell of the subject with an agent of Table 1 that inhibits the activity or expression of a proliferation-related polypeptide, cell cycle-related polypeptide, tumor suppressor polypeptide, or a polynucleotide encoding such polypeptides.
A method of characterizing neuroinflammation in a biological sample of a subject, the method comprising:
- a) sequencing RNA present in a biological sample comprising somatic cells of the subject to generate sequencing data;
- b) analyzing the sequencing data using the computer, in comparison to a reference sequence, at one or more loci associated with clonal hematopoiesis of indeterminate potential (CHIP), to generate a set of somatic copy number variations associated with CHIP present in the somatic cells;
- and
- c) calculating a burden of somatic copy number variations associated with CHIP in the biological sample relative to a reference subject, wherein an increase in the burden of somatic copy number variations in the subject, relative to the reference sequence, is indicative of neuroinflammation in the biological sample.
1 more element
A computer implemented method of determining a burden of somatic copy number variations in a biological sample of a subject, the method comprising:
- a) sequencing RNA present in a biological sample comprising somatic cells of the subject to generate sequencing data;
- b) analyzing the sequencing data using the computer, in comparison to a reference sequence, at one or more loci associated with CHIP, to generate a set of somatic copy number variations associated with CHIP present in the somatic cells;
- and
- c) calculating a burden of somatic copy number variations associated with CHIP in the biological sample relative to the reference sequence.
1 more element
A method of characterizing Alzheimer's disease in a biological sample of a subject, the method comprising:
- a) sequencing RNA present in a biological sample comprising somatic cells of the subject to generate sequencing data;
- b) analyzing the sequencing data using the computer, in comparison to a reference sequence, at one or more loci associated with CHIP, to generate a set of somatic copy number variations associated with CHIP present in the somatic cells;
- and
- c) calculating a burden of somatic copy number variations associated with CHIP in the biological sample relative to a reference subject, wherein an increase in the burden of somatic copy number variations in the subject, relative to the reference sequence, is indicative of Alzheimer's disease or a propensity to develop Alzheimer's disease in the subject.
1 more element
A method of characterizing neuroinflammation in a biological sample of a subject, the method comprising:
- a) sequencing RNA present in a biological sample comprising somatic cells of the subject to generate sequencing data;
- b) analyzing the sequencing data using the computer, in comparison to a reference sequence, at one or more loci associated with CHIP, to generate a set of somatic copy number variations associated with CHIP present in the somatic cells;
- c) sorting the sequencing data, using the set of somatic copy number variations associated with CHIP, into sequencing data from cells having copy number variations associated with CHIP (sCNV data) and sequencing data from cells not having copy number variations associated with CHIP (no sCNV data);
- and
- d) comparing expression levels for a set of genes between the sCNV data and the no SCNV data, wherein the set of genes comprises one or more of NEAT1, CD163, SLC11A1, SRGN, ASAP1, CADM1, RGS1, HIF1A, and GLUL, and wherein an increase in expression levels for the set of genes in the sCNV data as compared to the no sCNV data is indicative of neuroinflammation in the biological sample.
2 more elements
A method of characterizing Alzheimer's disease in a biological sample of a subject, the method comprising:
- a) sequencing RNA present in a biological sample comprising somatic cells of the subject to generate sequencing data;
- b) analyzing the sequencing data using the computer, in comparison to a reference sequence, at one or more loci associated with CHIP, to generate a set of somatic copy number variations associated with CHIP present in the somatic cells;
- c) sorting the sequencing data, using the set of somatic copy number variations associated with CHIP, into sequencing data from cells having copy number variations associated with CHIP (sCNV data) and sequencing data from cells not having copy number variations associated with CHIP (no sCNV data);
- and
- d) comparing expression levels for a set of genes between the sCNV data and the no SCNV data, wherein the set of genes comprises one or more of NEAT1, CD163, SLC11A1, SRGN, ASAP1, CADM1, RGS1, HIF1A, and GLUL, and wherein an increase in expression levels for the set of genes in the sCNV data as compared to the no sCNV data is indicative of Alzheimer's disease or a propensity to develop Alzheimer's disease in the subject.
2 more elements
Dependencies are inferred from the claim text.