WO2023034096A1 - Clonal hematopoiesis of indeterminate potential and protection from alzheimer's disease - Google Patents

Abstract

Compositions and methods are provided for classification and prognosis of susceptibility to development of Alzheimer's disease (AD). Surprisingly it is shown that individuals with clonal hematopoiesis of indeterminate potential (CHIP) have reduced risk of AD dementia or AD-related pathology. In an individual, the same CHIP-associated mutations found in circulating hematopoietic cells can also be detected in microglia cells of the brain; suggesting a role for mutant, marrow-derived cells in attenuating risk of AD.

Description

CLONAL HEMATOPOIESIS OF INDETERMINATE POTENTIAL AND PROTECTION FROM ALZHEIMER’S DISEASE CROSS-REFERENCE [0001] This application claims the benefit of U.S. Provisional Patent Application No.63/239,728 filed September 1, 2021, which application is incorporated herein by reference in its entirety. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH [0002] This invention was made with Government support under grant DP2-HL157540 awarded by the National Institutes of Health. The Government has certain rights in the invention. BACKGROUND [0003] Hematopoietic stem cells (HSCs) randomly accumulate somatic mutations during aging. While most of these mutations have no consequence, rare fitness-increasing mutations may allow an HSC to clonally expand. This age-associated expansion is termed clonal hematopoiesis of indeterminate potential (CHIP), is found in 10-30% of those older than 70, most commonly occurs due to mutations in transcriptional regulators such as DNMT3A, TET2, and ASXL1, and can be detected by sequencing of peripheral blood or bone marrow cells. These mutations are thought to provide a selective advantage to the hematopoietic stem cells in which they occur, and are detectable as clones in peripheral blood samples because the mutated stem cells maintain the ability to differentiate into circulating granulocytes, monocytes, and lymphocytes. [0004] While CHIP is a pre-malignant expansion of mutated blood stem cells that also associates with non-hematological disorders, as these mutations are also founding mutations for hematological neoplasms such as acute myeloid leukemia, it is unsurprising that CHIP associates with increased risk of developing these cancers. CHIP also associates with increased risk of atherosclerotic cardiovascular disease and death due to non-malignant causes. This link is believed to be causal, as mice that are deficient for Tet2 or Dnmt3a in hematopoietic cells develop larger atherosclerotic plaques, presumably due to altered gene expression in mutant macrophages which favors more rapid progression of the lesions. [0005] Alzheimer’s disease (AD) remains a leading cause of morbidity and mortality in the aged, but therapies that can effectively slow or halt its progression are lacking. Genome wide association studies have implicated functional alterations of microglia, the macrophage-like hematopoietic cells in the brain, as a major driver of AD risk. [0006] The present disclosure describes a relationship between CHIP and risk of AD. SUMMARY [0007] Compositions and methods are provided for classification and prognosis of an individual for susceptibility to development of Alzheimer’s disease (AD). Surprisingly it is shown that individuals with clonal hematopoiesis of indeterminate potential (CHIP) have reduced risk of AD dementia or AD-related pathology. In an individual, the same CHIP-associated mutations found in circulating hematopoietic cells can also be detected in microglia cells of the brain; suggesting a role for mutant, marrow-derived cells in attenuating risk of AD. In other embodiments, cell-free DNA is utilized to determine the presence of mutations associated with CHIP. [0008] In some embodiments a non-invasive method for determining risk of AD is provided, based on analysis of CHIP in a hematopoietic cell sample from an individual, where the presence of CHIP, e.g. as determined by a VAF > 0.08 in the population of hematopoietic cells, is associated with a decreased risk of developing AD. An assessment of the risk can be provided to the individual. The individual can be treated according to the level of risk for AD that was determined by the assessment of risk. In some embodiments the individual is greater than 50 years of age, greater than 55, greater than 60, greater than 65, greater than 70, greater than 75 years of age. [0009] In one embodiment of the invention, a method of determining risk of AD dementia or AD- related pathology is provided, comprising analyzing a patient sample(s) comprising hematopoietic cells. The cells can be isolated from a bone marrow, blood or blood-derived sample; or alternatively brain-derived microglial cells are used. A plurality of cells in the sample(s) are analyzed for the presence of clonality, usually by high throughput sequencing of polynucleotides isolated from the cell, for example whole exome sequencing, targeted sequencing of frequently mutated genes, etc. The number of cells analyzed may be at least 10², at least 10³, at least 10⁴, at least 10⁵ or more. The sequencing can be performed on bulk blood cells, e.g. PBLs, or on selected cell populations, e.g. myeloid cells, stem and progenitor cells, etc. The presence of CHIP can be defined by the presence of somatic mutations, where the most frequently mutated genes include, for example, DNMT3A, TET2, ASXL1, SF3B1, and GNB1. The variant allele fraction (VAF) can be determined, i.e. as the fraction of alleles present in the plurality of cells that comprise a specific somatic mutation. An individual is determined to be a CHIP carrier if the VAF is >0.08, >0.09, >0.1, >0.125, >0.15, >0.175, >0.2 or more. In some embodiments a cut-off of a VAF >0.2 is used to define an individual as having CHIP. The data can be compared to measurements from a control normal cell population. The data can be normalized for comparison. The presence of CHIP indicates an individual is preotected from development of AD. [0010] Clone size, which is represented by the VAF, is shown herein to be associated with reduced risk of AD dementia. VAF can represent the percentage of mutated DNA molecules relative to the total DNA input, or the percentage of cells with mutated DNA molecules relative to the total number of cells analyzed. Higher VAF is significantly associated with protection from AD dementia when modeled as a continuous variable. In some embodiments an individual is further genotyped for APOE alleles, where the protective effect is strongest in carriers of ε3ε3 or APOE ε4 alleles. [0011] In other embodiments of the invention a device or kit is provided for the analysis of patient samples. Such devices or kits will include reagents that specifically identify hematopoietic clonality indicative of the status of the patient, including without limitation reagents for sequencing one or more of DNMT3A, TET2, ASXL1, SF3B1, and GNB1, etc. The reagents can be provided in isolated form, or pre-mixed as a cocktail suitable for the methods of the invention. A kit can include instructions for using the plurality of reagents to determine data from the sample; and instuctions for statistically analyzing the data. The kits may be provided in combination with a system for analysis, e.g. a system implemented on a computer. Such a system may include a software component configured for analysis of data obtained by the methods of the invention. [0012] The methods disclosed herein include steps of data analysis, which may be provided as a program of instructions executable by computer and performed by means of software components loaded into the computer. Such methods include determining clonality, assessing sequence of mutations, determining VAF, and the like. Other bioinformatics methods are provided for determining and quantitating when the risk of AD is physiologically relevant. The method may further comprise providing a computer-generated report comprising the prognosis for risk. [0013] In an embodiment, the method further comprises selecting a treatment regimen for the patient based on the analysis. In an embodiment, the method further comprises providing a treatment course for the subject based on the analysis. Treatment regimens of interest can include decision-making for proceeding with extended hospital stay, medication, extended care at an intermediate facility, increased follow-up, and the like. In some embodiments a companion diagnostic is provided for determing whether an individual is suitable for treatment to slow AD progression. BRIEF DESCRIPTION OF THE DRAWINGS [0014] The invention is best understood from the following detailed description when read in conjunction with the accompanying drawings. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. Included in the drawings are the following figures. [0015] FIGS.1A-1E. CHIP is associated with protection from AD in multiple cohorts. A) Forest plot for risk of incident AD in CHIP carriers from Cardiovascular Health Study (CHS) and Framingham Heart Study (FHS) relative to non-carriers. Subdistribution hazard ratios (SHR), 95% confidence intervals (CI95) and Wald p-values were calculated for each covariate from competing risks regression models which included age at blood draw, sex, and APOE genotype as covariates. Results from CHS and FHS were then meta-analyzed using a fixed-effects model for the two cohorts (see Figure S1 for full regression results). B) Forest plot for risk of AD in CHIP carriers relative to non-carriers from the AD Sequencing Project (ADSP) with APOE ε3ε3 genotype. Odds ratio (OR), 95% confidence interval (CI95) and Wald p-value were calculated from a logistic regression model that also included age at time of blood draw and sex as covariates. C) Fixed-effects meta-analysis for risk of AD in CHIP carriers using logistic regression in ADSP, FHS, and CHS. D) Plot of odds ratio (OR) and 95% confidence interval (CI95) for increased CERAD neuritic plaque score in ADSP participants without a dementia diagnosis from an ordinal logistic regression model. The covariates included in the model (age at time of exome sequencing blood draw, APOE genotype, sex, and CHIP status) are shown. The p-values were calculated by comparing the t-statistic for each covariate against a standard normal distribution. E) Plot of odds ratio (OR) and 95% confidence interval (CI95) for increased Braak stage in ADSP participants without a dementia diagnosis from an ordinal logistic regression model. The covariates included in the model (age at time of exome sequencing blood draw, APOE genotype, sex, and CHIP status) are shown. The p-values were calculated by comparing the t-statistic for each covariate against a standard normal distribution. [0016] FIGS.2A-2C. Associations of CHIP to AD by APOE genotype and mutated driver gene. A) Kaplan-Meier curve showing AD-free probability in CHIP non-carriers (left) and carriers (right)_, stratified by APOE genotype. Analysis was restricted to those older than 70 at time of blood draw. B) Forest plot for effect of CHIP on AD risk in participants from CHS and FHS stratified by APOE genotype. Participants were binned into those with neutral (APOE ε3ε3), low risk (APOE ε2ε2 and ε2ε3), and high-risk (any APOE ε4 allele) groups. Subdistribution hazard ratios (SHR), 95% confidence intervals (CI95) and Wald p-values were calculated for each covariate (age at time blood draw for sequencing, sex, CHIP carrier status) from competing risks regression models, and results from FHS and CHS were then meta-analyzed using a fixed-effects model. C) Plot of odds ratios for effect of mutated CHIP gene on AD in participants from the TOPMed cohorts (CHS and FHS) and ADSP. Odds ratios (OR), 95% confidence intervals (CI95) and Wald p-values were calculated for each covariate (age at time blood draw for sequencing, sex, cohort, and APOE genotype) from logistic regression models, and results from the TOPMed cohorts and ADSP were then meta-analyzed using a fixed-effects model. [0017] FIGS.3A-3C. CHIP variants can be found in the microglia-enriched fraction of brain. A) Barplot of putative CHIP mutations identified from whole exome sequencing of brain DNA from 1,775 persons in ADSP. B) Schematic of experimental workflow: Autopsy samples from occipital cortex, cerebellum and putamen were digested to prepare single nuclei suspensions. Nuclei were then stained and sorted on using antibodies to C-Maf⁺ (marker of myeloid cells) and NeuN+ (Marker of Neuronal cells), followed by amplicon sequencing for CHIP variants. C) Barplot of the variant allele fraction (VAF) of the CHIP variants from 8 donors (ACT1 to ACT8). For each sample, the VAF in the blood and in the brain C-Maf⁺ NeuN- population are shown. Occipital cortex was available for all 8 donors. A bar for cerebellum or putamen is shown if available, otherwise NA in the corresponding color designates lack of an available sample (purple for cerebellum and red for putamen). The CHIP mutations carried by each participant are reported in the box on the right of the barplot. [0018] FIGS.4A-4E. scATAC-seq of brain samples from CHIP carriers reveals that the mutated cells are similar to microglia and comprise a large proportion of the microglial pool. A) scATAC- seq profiles of 111,190 cells from our dataset and the Corces et. al. adult human brain dataset. Each dot represents the scATAC-seq profile of one cell and is colored by its assigned cluster. B) scATAC-seq profiles of all cells colored by which sample it originated from. Samples from Corces et. al. are aggregated and shown in grey. Sorted samples were from the c-Maf+ NeuN- gate. C) Pseudo-bulk tracks for selected gene loci. The top 5 tracks show scATAC-seq coverage of cells from the indicated sample (or aggregated Corces et.al. samples) within C9, the microglia cluster. The monocyte and classical dendritic cell (cDC) tracks are from the Satpathy et. al. hematopoiesis dataset. D) Fraction of cells in cluster C9 (microglia) for sorted versus unsorted brain samples. E) Proportion of microglia (mg) bearing a CHIP mutation in each sample, calculated by dividing the percentage of cells in cluster 9 in each unsorted sample by 2 times the VAF of the CHIP mutation for that sample. The brain regions are abbreviated as Ce for Cerebellum, OC for Occipital cortex, and P for putamen. [0019] FIG.5. CHIP is associated with protection from AD in CHS and FHS. Forest plot of risk factors for incident Alzheimer’s disease (AD) in Cardiovascular Health Study (CHS) and Framingham Heart Study (FHS). The covariates included in the model (age at time of whole genome sequencing blood draw, APOE genotype, sex, and CHIP status) are shown. Hazard ratios (HR), 95% confidence intervals (CI95) and Wald p-values were calculated for each covariate from Cox proportional hazards regression models, which were then meta-analyzed using a fixed-effects model for the two cohorts. [0020] FIG.6. The VAF distribution is different in TOPMed and ADSP due to higher sequencing depth in ADSP. Density plots of VAF from all CHIP carriers in ADSP (left) or in CHIP carriers with VAF greater than 0.08 (right) compared to VAF distribution from TOPMed CHIP carriers (red) in each plot. [0021] FIG.7. Sorting of nuclei from brains of CHIP carriers can be used to enrich for the mutant cells. Flow cytometry gating strategy for nuclei sorting for the 8 brain samples using C-MAF and NeuN markers. The arrow points to the C-MAF⁺ NeuN- sorted population and the VAF is indicated for each sample. The brain regions are abbreviated as Ce for Cerebellum, OC for Occipital cortex, and P for putamen. [0022] FIGS.8A-8C. High-quality scATAC-seq libraries from ACT brain samples. Quality control metrics for each cell in the indicated scATAC-seq sample. Aggregated Corces 2020 samples are included for reference. (A) Enrichment of fragments in transcription start sites (TSS), (B) number of fragments, and (C) fraction of reads in peaks (FRIP) for each cell. The brain regions are abbreviated as Ce for Cerebellum, OC for Occipital cortex, and P for putamen. [0023] FIGS. 9A-9C. Marker genes for scATAC-seq clusters. GeneScore markers used to identify cell types from scATAC-seq data. Pseudo-bulk tracks shown for additional genes. Histogram of the number of differential peaks (Wilcoxon test, FDR < 0.1, |log2(fold change)| > 1) comparing cells within Cluster 9 for different pairs of samples. Left: all pairs of Corces 2020 samples. Right: all pairs of samples generated in this study. The brain regions are abbreviated as Ce for Cerebellum, OC for Occipital cortex, and P for putamen. DETAILED DESCRIPTION [0024] Compositions and methods are provided for classification and prognosis of susceptibility to development of Alzheimer’s disease (AD). Surprisingly it is shown that individuals with clonal hematopoiesis of indeterminate potential (CHIP) have reduced risk of AD dementia or AD-related pathology. Without being limited by the theory, it is believed that mutations associated with CHIP confer circulating precursor cells with an enhanced ability to engraft in the brain, to differentiate into microglia once engrafted, and/or to clonally expand relative to unmutated cells in the brain microenvironment. These non-mutually exclusive possibilities may provide protection from AD by supplementing the phagocytic capacity of the endogenous microglial system during aging. Alternatively, or in addition, the mutations may alter the functionality of the engrafted myeloid cells in a manner that promotes clearance of pathologic amyloid or tau. [0025] Before the present methods and compositions are described, it is to be understood that this invention is not limited to particular method or composition described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims. [0026] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention. [0027] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. It is understood that the present disclosure supercedes any disclosure of an incorporated publication to the extent there is a contradiction. [0028] It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a cell" includes a plurality of such cells and reference to "the peptide" includes reference to one or more peptides and equivalents thereof, e.g. polypeptides, known to those skilled in the art, and so forth. [0029] The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed. [0030] The terms "subject," "individual," and "patient" are used interchangeably herein to refer to a vertebrate, preferably a mammal, more preferably a human. Mammalian species that provide samples for analysis include canines; felines; equines; bovines; ovines; etc. and primates, particularly humans. Animal models, particularly small mammals, e.g. murine, lagomorpha, etc. can be used for experimental investigations. The methods of the invention can be applied for veterinary purposes. [0031] As used herein, the term "theranosis" refers to the use of results obtained from a diagnostic method to direct the selection of, maintenance of, or changes to a therapeutic regimen, including but not limited to the choice of one or more therapeutic agents, changes in dose level, changes in dose schedule, changes in mode of administration, and changes in formulation. Diagnostic methods used to inform a theranosis can include any that provides information on the state of a disease, condition, or symptom. [0032] The terms "therapeutic agent", "therapeutic capable agent" or "treatment agent" are used interchangeably and refer to a molecule or compound that confers some beneficial effect upon administration to a subject. The beneficial effect includes enablement of diagnostic determinations; amelioration of a disease, symptom, disorder, or pathological condition; reducing or preventing the onset of a disease, symptom, disorder or condition; and generally counteracting a disease, symptom, disorder or pathological condition. [0033] As used herein, "treatment" or "treating," or "palliating" or "ameliorating" are used interchangeably. These terms refer to an approach for obtaining beneficial or desired results including but not limited to a therapeutic benefit and/or a prophylactic benefit. By therapeutic benefit is meant any therapeutically relevant improvement in or effect on one or more diseases, conditions, or symptoms under treatment. For prophylactic benefit, the compositions may be administered to a subject at risk of developing a particular disease, condition, or symptom, or to a subject reporting one or more of the physiological symptoms of a disease, even though the disease, condition, or symptom may not have yet been manifested. [0034] The term "effective amount" or "therapeutically effective amount" refers to the amount of an agent that is sufficient to effect beneficial or desired results. The therapeutically effective amount will vary depending upon the subject and disease condition being treated, the weight and age of the subject, the severity of the disease condition, the manner of administration and the like, which can readily be determined by one of ordinary skill in the art. The term also applies to a dose that will provide an image for detection by any one of the imaging methods described herein. The specific dose will vary depending on the particular agent chosen, the dosing regimen to be followed, whether it is administered in combination with other compounds, timing of administration, the tissue to be imaged, and the physical delivery system in which it is carried. [0035] "Suitable conditions" shall have a meaning dependent on the context in which this term is used. That is, when used in connection with an antibody, the term shall mean conditions that permit an antibody to bind to its corresponding antigen. When used in connection with contacting an agent to a cell, this term shall mean conditions that permit an agent capable of doing so to enter a cell and perform its intended function. In one embodiment, the term "suitable conditions" as used herein means physiological conditions. [0036] To “analyze” includes determining a set of values associated with a sample by measurement of a marker, in particular determining the prevalence of a mutant allele in a hematopoietic cell population, and determining the VAF, which may be compared against a reference, or control sample. The variant alleles can be analyzed by any of various conventional methods known in the art, particularly sequencing, PCR, etc. To “analyze” can include performing a statistical analysis, e.g. normalization of data, determination of statistical significance, determination of statistical correlations, clustering algorithms, and the like. [0037] A “sample” in the context of the present teachings refers to any biological sample that is isolated from a subject, generally a sample comprising circulating hematopoietic cells. A sample can include, without limitation, an aliquot of body fluid, whole blood, PBMC (white blood cells or leucocytes), lymphatic fluid, ascites fluid, and interstitial or extracellular fluid. Microglia can be obtained from a CSF sample. "Blood sample" can refer to whole blood or a fraction thereof, including blood cells, peripheral blood monocytes, white blood cells or leucocytes. Samples can be obtained from a subject by means including but not limited to venipuncture, biopsy, needle aspirate, lavage, scraping, surgical incision, or intervention or other means known in the art. The number of cells analyzed from a sample may be at least 10², at least 10³, at least 10⁴, at least 10⁵ or more. [0038] The methods of the present disclosure involve sequencing whole exome or target loci, as well as analyzing sequence data. Various methods and protocols for DNA sequencing and analysis are well-known in the art and are described herein. For example, DNA sequencing may be accomplished using high-throughput DNA sequencing techniques. Examples of next generation and high-throughput sequencing include, for example, massively parallel signature sequencing, polony sequencing, 454 pyrosequencing, Illumina (Solexa) sequencing with HiSeq, MiSeq, and other platforms, SOLiD sequencing, ion semiconductor sequencing (Ion Torrent), DNA nanoball sequencing, heliscope single molecule sequencing, single molecule real time (SMRT) sequencing, MassARRAY®, and Digital Analysis of Selected Regions (DANSR™). See, e.g., Stein RA (1 September 2008). "Next-Generation Sequencing Update". Genetic Engineering & Biotechnology News 28 (15); Quail, Michael; Smith, Miriam E; Coupland, Paul; Otto, Thomas D; Harris, Simon R; Connor, Thomas R; Bertoni, Anna; Swerdlow, Harold P; Gu, Yong (1 January 2012). "A tale of three next generation sequencing platforms: comparison of Ion torrent, pacific biosciences and illumina MiSeq sequencers". BMC Genomics 13 (1): 341 ; Liu, Lin; Li, Yinhu; Li, Siliang; Hu, Ni; He, Yimin; Pong, Ray; Lin, Danni; Lu, Lihua; Law, Maggie (1 January 2012). "Comparison of Next-Generation Sequencing Systems". Journal of Biomedicine and Biotechnology 2012: 1-11; Qualitative and quantitative genotyping using single base primer extension coupled with matrix-assisted laser desorption/ionization time-of -flight mass spectrometry (MassARRAY®). Methods Mol Biol.2009;578:307-43; Chu T, Bunce K, Hogge WA, Peters DG. A novel approach toward the challenge of accurately quantifying fetal DNA in maternal plasma. Prenat Diagn 2010;30: 1226-9; and Suzuki N, Kamataki A, Yamaki J, Homma Y. Characterization of circulating DNA in healthy human plasma. Clinica chimica acta; international journal of clinical chemistry 2008;387:55-8). Similarly, software programs for primary and secondary analysis of sequence data are well known in the art. [0039] A “dataset” is a set of numerical values resulting from evaluation of a sample (or population of samples) under a desired condition, for example a dataset may comprise DNA sequence information. The values of the dataset can be obtained, for example, by experimentally obtaining measures from a sample and constructing a dataset from these measurements; or alternatively, by obtaining a dataset from a service provider such as a laboratory, or from a database or a server on which the dataset has been stored. Similarly, the term “obtaining a dataset associated with a sample” encompasses obtaining a set of data determined from at least one sample. Obtaining a dataset encompasses obtaining a sample, and processing the sample to experimentally determine the data, e.g., via measuring antibody binding, or other methods of quantitating a signaling response. The phrase also encompasses receiving a set of data, e.g., from a third party that has processed the sample to experimentally determine the dataset. [0040] “Measuring” or “measurement” in the context of the present teachings refers to determining the presence, absence, quantity, amount, or effective amount of a a variant allelic fraction (VAF) in a clinical or subject-derived sample. [0041] “Affinity reagent”, or “specific binding member” may be used to refer to an affinity reagent, such as an antibody, ligand, etc. that selectively binds to a protein or marker of the invention, which may be used in subsetting of hematopoietic cells. The term "affinity reagent" includes any molecule, e.g., peptide, nucleic acid, small organic molecule. For some purposes, an affinity reagent selectively binds to a cell surface marker. For other purposes an affinity reagent selectively binds to a cellular signaling protein. [0042] In some embodiments, the affinity reagent is a peptide, polypeptide, oligopeptide or a protein, particularly antibodies and specific binding fragments and variants thereof. The peptide, polypeptide, oligopeptide or protein can be made up of naturally occurring amino acids and peptide bonds, or synthetic peptidomimetic structures. Thus "amino acid", or "peptide residue", as used herein include both naturally occurring and synthetic amino acids. Proteins including non-naturally occurring amino acids can be synthesized or in some cases, made recombinantly; see van Hest et al., FEBS Lett 428:(l-2) 68-70 May 22, 1998 and Tang et al., Abstr. Pap Am. Chem. S218: U138 Part 2 Aug.22, 1999, both of which are expressly incorporated by reference herein. [0043] The term "antibody" includes full length antibodies and antibody fragments, and can refer to a natural antibody from any organism, an engineered antibody, or an antibody generated recombinantly for experimental, therapeutic, or other purposes as further defined below. Examples of antibody fragments, as are known in the art, such as Fab, Fab', F(ab')2, Fv, scFv, or other antigen-binding subsequences of antibodies, either produced by the modification of whole antibodies or those synthesized de novo using recombinant DNA technologies. The term "antibody" comprises monoclonal and polyclonal antibodies. Antibodies can be antagonists, agonists, neutralizing, inhibitory, or stimulatory. They can be humanized, glycosylated, bound to solid supports, and possess other variations. [0044] The methods the invention may utilize affinity reagents comprising a label, labeling element, or tag. By label or labeling element is meant a molecule that can be directly (i.e., a primary label) or indirectly (i.e., a secondary label) detected; for example a label can be visualized and/or measured or otherwise identified so that its presence or absence can be known. [0045] Sorting, or isolating step can entail fluorescence-activated cell sorting (FACS) techniques, where FACS is used to select cells from the population containing a particular surface marker, or the selection step can entail the use of magnetically responsive particles as retrievable supports for target cell capture and/or background removal. A variety of FACS systems are known in the art and can be used in the methods of the invention (see e.g., W099/54494, filed Apr.16, 1999; U.S. Ser. No.20010006787, filed Jul.5, 2001, each expressly incorporated herein by reference). [0046] In some embodiments, a FACS cell sorter (e.g. a FACSVantage™ Cell Sorter, Becton Dickinson Immunocytometry Systems, San Jose, Calif.) is used to sort and collect cells based on their phenotype. Other flow cytometers that are commercially available include the LSR II and the Canto II both available from Becton Dickinson. See Shapiro, Howard M., Practical Flow Cytometry, 4th Ed., John Wiley & Sons, Inc., 2003 for additional information on flow cytometers. [0047] The present invention incorporates information disclosed in other applications and texts. The following patent and other publications are hereby incorporated by reference in their entireties: Alberts et al., The Molecular Biology of the Cell, 4th Ed., Garland Science, 2002; Vogelstein and Kinzler, The Genetic Basis of Human Cancer, 2d Ed., McGraw Hill, 2002; Michael, Biochemical Pathways, John Wiley and Sons, 1999; Weinberg, The Biology of Cancer, 2007; Immunobiology, Janeway et al. 7th Ed., Garland, and Leroith and Bondy, Growth Factors and Cytokines in Health and Disease, A Multi Volume Treatise, Volumes 1A and IB, Growth Factors, 1996. [0048] Unless otherwise apparent from the context, all elements, steps or features of the invention can be used in any combination with other elements, steps or features. [0049] General methods in molecular and cellular biochemistry can be found in such standard textbooks as Molecular Cloning: A Laboratory Manual, 3rd Ed. (Sambrook et al., Harbor Laboratory Press 2001); Short Protocols in Molecular Biology, 4th Ed. (Ausubel et al. eds., John Wiley & Sons 1999); Protein Methods (Bollag et al., John Wiley & Sons 1996); Nonviral Vectors for Gene Therapy (Wagner et al. eds., Academic Press 1999); Viral Vectors (Kaplift & Loewy eds., Academic Press 1995); Immunology Methods Manual (I. Lefkovits ed., Academic Press 1997); and Cell and Tissue Culture: Laboratory Procedures in Biotechnology (Doyle & Griffiths, John Wiley & Sons 1998). Reagents, cloning vectors, and kits for genetic manipulation referred to in this disclosure are available from commercial vendors such as BioRad, Stratagene, Invitrogen, Sigma-Aldrich, and ClonTech. [0050] The invention has been described in terms of particular embodiments found or proposed by the present inventor to comprise preferred modes for the practice of the invention. It will be appreciated by those of skill in the art that, in light of the present disclosure, numerous modifications and changes can be made in the particular embodiments exemplified without departing from the intended scope of the invention. Due to biological functional equivalency considerations, changes can be made in protein structure without affecting the biological action in kind or amount. All such modifications are intended to be included within the scope of the appended claims. Methods of Prognosis and Therapy [0051] In a embodiment of the invention, a method of determining risk of AD dementia or AD- related pathology is provided, comprising: obtaining a patient sample(s) comprising hematopoietic cells; sequencing genomes of cells present in the sample; determining with a computer algorithm the variant allele fraction (VAF) in the population; providing an assessment of AD susceptibility based on VAF. The sample may additionally be specifically typed for APOE alleles. The individual can be treated in accordance with the findings. [0052] The hematopoietic cells can be isolated from a bone marrow, blood or blood-derived sample. Brain-derived microglial cells are also informative. The sample(s) is analyzed for the presence of clonality, usually by high throughput sequencing, for example whole exome sequencing, targeted sequencing of frequently mutated genes, etc. The sequencing can be performed on bulk blood cells, e.g. PBLs, or on selected cell populations, e.g. myeloid cells, stem and progenitor cells, etc. CHIP is predominantly defined by the presence of somatic mutations, where the most frequently mutated genes include, for example, DNMT3A, TET2, ASXL1, SF3B1, and GNB1. The variant allele fraction (VAF) can be determined, i.e. as the fraction of alleles in the sample that comprise the somatic mutation. An individual may be determined to be a CHIP carrier if the VAF is >0.08; and the cut-off may be >0.09, >0.1, >0.125, >0.15, >0.175, >0.2 or more. In some embodiments a cut-off VAF < 0.2 is used for assigning a patient to an AD low-risk group. The data can be compared to measurements from a control normal cell population. The data can be normalized for comparison. [0053] Clone size, which is approximated by the VAF, is shown herein to be associated with reduced risk of AD dementia. Higher VAF is significantly associated with protection from AD dementia when modeled as a continuous variable. In some embodiments an individual is further genotyped for APOE alleles, where the protective effect is strongest in carriers of ε3ε3 or APOE ε4 alleles. [0054] VAF can represent the percentage of mutated DNA molecules relative to the total DNA input, or the percentage of cells with mutated DNA molecules relative to the total number of cells analyzed. Most cancer-associated somatic mutations affect only one allele (heterozygous), and thus a variant allele frequency of 50% implies that 100% of cells carry somatic mutations. Variant allele frequency depends on the size of the clone, heterogeneity, the amount of non-clonal healthy cells (eg, non-clonal lymphocytes or stromal cells from bone marrow biopsy), and the co- occurrence of numerical chromosomal alterations. The analysis may take into account not only the binary information of the presence or absence of particular mutations, but also the percentage of affected cells (clonal burden). [0055] When reviewing the results of next-generation sequencing panel testing, some germline variants may be present in somatic reports. How these are codified and interpreted can vary by report and can be a potential source of confusion. In some embodiments concurrent DNA testing from non-haematopoietic tissues (eg, skin fibroblasts) is provided as germline controls. [0056] Genotyping hematopoietic cells and/or detection, identification and/or quantitation of the mutations can utilize sequencing. Sequencing can be accomplished using high-throughput systems using nucleic acids described herein such as genomic DNA, cDNA derived from RNA transcripts or RNA as a template. Sequencing may comprise massively parallel sequencing. [0057] In some embodiments, high-throughput sequencing involves the use of technology available by Helicos BioSciences Corporation (Cambridge, Massachusetts) such as the Single Molecule Sequencing by Synthesis (SMSS) method. In some embodiments, high-throughput sequencing involves the use of technology available by 454 Lifesciences, Inc. (Branford, Connecticut) such as the Pico Titer Plate device which includes a fiber optic plate that transmits chemiluminescent signal generated by the sequencing reaction to be recorded by a CCD camera in the instrument. This use of fiber optics allows for the detection of a minimum of 20 million base pairs in 4.5 hours. [0058] In some embodiments, high-throughput sequencing is performed using Clonal Single Molecule Array (Solexa, Inc.) or sequencing-by-synthesis (SBS) utilizing reversible terminator chemistry. These technologies are described in part in US Patent Nos. 6,969,488; 6,897,023; 6,833,246; 6,787,308; and US Publication Application Nos. 200401061 30; 20030064398; 20030022207; and Constans, A, The Scientist 2003, 17(13):36. [0059] In some embodiments, high-throughput sequencing of RNA or DNA can take place using AnyDot.chips (Genovoxx, Germany), which allows for the monitoring of biological processes (e.g., miRNA expression or allele variability (SNP detection). In particular, the AnyDot-chips allow for 10x - 50x enhancement of nucleotide fluorescence signal detection. Other high-throughput sequencing systems include those disclosed in Venter, J., et al. Science 16 February 2001; Adams, M. et al, Science 24 March 2000; and M. J, Levene, et al. Science 299:682-686, January 2003; as well as US Publication Application No.20030044781 and 2006/0078937. The growing of the nucleic acid strand and identifying the added nucleotide analog may be repeated so that the nucleic acid strand is further extended and the sequence of the target nucleic acid is determined. [0060] The methods disclosed herein may comprise amplification of DNA. Amplification may comprise PCR-based amplification. Alternatively, amplification may comprise nonPCR-based amplification. Amplification of DNA may comprise using bead amplification followed by fiber optics detection as described in Marguiles et al. "Genome sequencing in microfabricated high- density pricolitre reactors", Nature, doi: 10.1038/nature03959; and well as in US Publication Application Nos.20020012930; 20030058629; 20030100102; 20030148344 ; 20040248161 ; 20050079510,20050124022; and 20060078909. Amplification of the nucleic acid may comprise use of one or more polymerases. The polymerase may be a DNA polymerase. The polymerase may be a RNA polymerase. The polymerase may be a high fidelity polymerase. The polymerase may be KAPA HiFi DNA polymerase. The polymerase may be Phusion DNA polymerase. Amplification may comprise 20 or fewer amplification cycles. Amplification may comprise 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, or 9 or fewer amplification cycles. Amplification may comprise 18 or fewer amplification cycles. Amplification may comprise 16 or fewer amplification cycles. Amplification may comprise 15 or fewer amplification cycles. [0061] An increase in clonality of hematopoietic cells (CHIP) is shown herein to be associated with a decreased risk of developing AD. Alzheimer disease causes progressive cognitive deterioration and is characterized by beta-amyloid deposits and neurofibrillary tangles in the cerebral cortex and subcortical gray matter. Most cases of Alzheimer disease are sporadic, with late onset (≥ 65 years) and unclear etiology. Risk of developing the disease is best predicted by age. However, about 5 to 15% of cases are familial; half of these cases have an early (presenile) onset (< 65 years) and are typically related to specific genetic mutations. [0062] Mutations in genes for the amyloid precursor protein, presenilin I, and presenilin II may lead to autosomal dominant forms of Alzheimer disease, typically with presenile onset. In affected patients, the processing of amyloid precursor protein is altered, leading to deposition and fibrillar aggregation of beta-amyloid; beta-amyloid is the main component of senile plaques, which consist of degenerated axonal or dendritic processes, astrocytes, and glial cells around an amyloid core. Beta-amyloid may also alter kinase and phosphatase activities in ways that eventually lead to hyperphosphorylation of tau (a protein that stabilizes microtubules) and formation of neurofibrillary tangles. [0063] In some embodiments an individual is further genotyped for APOE alleles, where the protective effect is strongest in carriers of ε3ε3 or APOE ε4 alleles. Apo E proteins influence beta- amyloid deposition, cytoskeletal integrity, and efficiency of neuronal repair. Without consideration of CHIP, the risk of Alzheimer disease is substantially increased in people with two ε4 alleles and may be decreased in those who have the ε2 allele. For people with two ε4 alleles, risk of developing Alzheimer disease by age 75 is about 10 to 30 times that for people without the allele. [0064] APOE gene coding is polymorphic and encodes three apoE protein isoforms: E2, E3 and E4. These isoforms differ at the amino acid residues 112 and 158. Isoform E2 has cysteine residues at both sites, E4 has arginine residues at both sites, while E3, the most common form, has a cysteine at position 112 and an arginine at position 158. The isoform E4 is associated with higher levels of cholesterol and increased risk for coronary heart and Alzheimer’s diseases (AD). In contrast, isoform E2 shows a protective effect against Alzheimer’s disease, but it is associated with familial type III hyperlipoproteinemia. [0065] Several methods are commonly used for genotyping the three major APOE haplotypes. The most frequently used methods are: PCR-RFLP (Polymerase Chain Reaction-Restriction Fragment Length Polymorphism), capillary electrophoresis, PCR plus sequencing or mass spectrometry, ARMS-PCR (Amplification Refractory Mutation System-PCR), and SSP-PCR (Simple Sequence Specific Primer-PCR), RT-PCR (Real Time-PCR) detection by fluorescence melting curves, FRET (Fluorescent Resonance Energy Transfer), allele specific RT-PCR, and TaqMan probes. All of these APOE gene-based methods are very effective. [0066] Alternative biochemical (non-genetic) methods are in use for the sensitive characterization of apoE isoforms from biological fluids such as plasma or CSF. The most commonly used are isoelectric focusing (IEF)-immunoblotting and sandwich ELISA, both in in- house and commercial assay (e.g. Biovision #K4699-100, MBL International #7635) setups. ELISA techniques use a pair of anti-apo-E antibodies (capture and reporter antibodies, being one of them specific for the E4 isoform), plus a secondary labeled-antibody for the sensitive detection. This method relies on the simplification of ELISA procedure, or other techniques such as turbidimetry, by exploiting the binding properties of apoE to polystyrene, precluding the use of a capture antibody or previous separation procedures, and allowing the sensitive detection of the apoE4 protein in diluted biological samples. [0067] In some aspects of the subject methods, an individual is selected and treated for AD in accordance with the findings of risk as disclosed herein. In an embodiment, treatment is selected from administration of aducanumab; galantamine, rivastigmine, and/or donepezil; memantine and a combination medication of memantine and donepezil. [0068] Several prescription drugs are already approved by the U.S. Food and Drug Administration (FDA) to help manage symptoms in people with Alzheimer’s disease. The FDA has provided accelerated approval for aducanumab, which helps to reduce amyloid deposits in the brain and may help slow the progression of Alzheimer’s. The present methods provide for useful stratification of individuals with respect to the need for such therapy. Galantamine, rivastigmine, and donepezil are cholinesterase inhibitors that are prescribed for mild to moderate Alzheimer’s symptoms. These drugs may help reduce or control some cognitive and behavioral symptoms. [0069] Memantine, an N-methyl D-aspartate (NMDA) antagonist, is prescribed to treat moderate to severe Alzheimer’s disease. This drug’s main effect is to decrease symptoms, which could enable some people to maintain certain daily functions a little longer than they would without the medication. For example, memantine may help a person in the later stages of the disease maintain his or her ability to use the bathroom independently for several more months, a benefit for both the person with Alzheimer's and caregivers. The FDA has also approved donepezil, the rivastigmine patch, and a combination medication of memantine and donepezil for the treatment of moderate to severe Alzheimer’s. [0070] Dosage and frequency may vary depending on the half-life of the agent in the patient. It will be understood by one of skill in the art that such guidelines will be adjusted for the molecular weight of the active agent, the clearance from the blood, the mode of administration, and other pharmacokinetic parameters. The dosage may also be varied for localized administration, e.g. intranasal, inhalation, etc., or for systemic administration, e.g. i.m., i.p., i.v., oral, and the like. [0071] An active agent can be administered by any suitable means, including topical, oral, parenteral, intrapulmonary, and intranasal. Parenteral infusions include intramuscular, intravenous (bolus or slow drip), intraarterial, intraperitoneal, intrathecal or subcutaneous administration. An agent can be administered in any manner which is medically acceptable. This may include injections, by parenteral routes such as intravenous, intravascular, intraarterial, subcutaneous, intramuscular, intratumor, intraperitoneal, intraventricular, intraepidural, or others as well as oral, nasal, ophthalmic, rectal, or topical. Sustained release administration is also specifically included in the disclosure, by such means as depot injections or erodible implants. [0072] As noted above, an agent can be formulated with an a pharmaceutically acceptable carrier (one or more organic or inorganic ingredients, natural or synthetic, with which a subject agent is combined to facilitate its application). A suitable carrier includes sterile saline although other aqueous and non-aqueous isotonic sterile solutions and sterile suspensions known to be pharmaceutically acceptable are known to those of ordinary skill in the art. An "effective amount" refers to that amount which is capable of ameliorating or delaying progression of the diseased, degenerative or damaged condition. An effective amount can be determined on an individual basis and will be based, in part, on consideration of the symptoms to be treated and results sought. An effective amount can be determined by one of ordinary skill in the art employing such factors and using no more than routine experimentation. [0073] An agent can be administered as a pharmaceutical composition comprising a pharmaceutically acceptable excipient. The preferred form depends on the intended mode of administration and therapeutic application. The compositions can also include, depending on the formulation desired, pharmaceutically-acceptable, non-toxic carriers or diluents, which are defined as vehicles commonly used to formulate pharmaceutical compositions for animal or human administration. The diluent is selected so as not to affect the biological activity of the combination. Examples of such diluents are distilled water, physiological phosphate-buffered saline, Ringer's solutions, dextrose solution, and Hank's solution. In addition, the pharmaceutical composition or formulation may also include other carriers, adjuvants, or nontoxic, nontherapeutic, nonimmunogenic stabilizers and the like. [0074] As used herein, compounds which are "commercially available" may be obtained from commercial sources including but not limited to Acros Organics (Pittsburgh PA), Aldrich Chemical (Milwaukee WI, including Sigma Chemical and Fluka), Apin Chemicals Ltd. (Milton Park UK), Avocado Research (Lancashire U.K.), BDH Inc. (Toronto, Canada), Bionet (Cornwall, U.K.), Chemservice Inc. (West Chester PA), Crescent Chemical Co. (Hauppauge NY), Eastman Organic Chemicals, Eastman Kodak Company (Rochester NY), Fisher Scientific Co. (Pittsburgh PA), Fisons Chemicals (Leicestershire UK), Frontier Scientific (Logan UT), ICN Biomedicals, Inc. (Costa Mesa CA), Key Organics (Cornwall U.K.), Lancaster Synthesis (Windham NH), Maybridge Chemical Co. Ltd. (Cornwall U.K.), Parish Chemical Co. (Orem UT), Pfaltz & Bauer, Inc. (Waterbury CN), Polyorganix (Houston TX), Pierce Chemical Co. (Rockford IL), Riedel de Haen AG (Hannover, Germany), Spectrum Quality Product, Inc. (New Brunswick, NJ), TCI America (Portland OR), Trans World Chemicals, Inc. (Rockville MD), Wako Chemicals USA, Inc. (Richmond VA), Novabiochem and Argonaut Technology. [0075] Compounds useful for co-administration with the active agents of the invention can also be made by methods known to one of ordinary skill in the art. As used herein, "methods known to one of ordinary skill in the art" may be identified though various reference books and databases. Suitable reference books and treatises that detail the synthesis of reactants useful in the preparation of compounds of the present invention, or provide references to articles that describe the preparation, include for example, "Synthetic Organic Chemistry", John Wiley & Sons, Inc., New York; S. R. Sandler et al., "Organic Functional Group Preparations," 2nd Ed., Academic Press, New York, 1983; H. O. House, "Modern Synthetic Reactions", 2nd Ed., W. A. Benjamin, Inc. Menlo Park, Calif.1972; T. L. Gilchrist, “Heterocyclic Chemistry”, 2nd Ed., John Wiley & Sons, New York, 1992; J. March, “Advanced Organic Chemistry: Reactions, Mechanisms and Structure”, 4th Ed., Wiley-Interscience, New York, 1992. Specific and analogous reactants may also be identified through the indices of known chemicals prepared by the Chemical Abstract Service of the American Chemical Society, which are available in most public and university libraries, as well as through on-line databases (the American Chemical Society, Washington, D.C., may be contacted for more details). Chemicals that are known but not commercially available in catalogs may be prepared by custom chemical synthesis houses, where many of the standard chemical supply houses (e.g., those listed above) provide custom synthesis services. [0076] In some embodiments an individual is monitored for indicia of AD in combination with the methods disclosed herein. Methods for measuring cognitive or visual function and identifying an individual having a cognitive or visual impairment are well known in the art, any of which may be used to identify an individual in need of assessment by the subject methods. [0077] The two pathologic hallmarks of Alzheimer disease are extracellular beta-amyloid deposits (in senile plaques); and intracellular neurofibrillary tangles (paired helical filaments). The beta-amyloid deposition and neurofibrillary tangles lead to loss of synapses and neurons, which results in gross atrophy of the affected areas of the brain, typically starting at the mesial temporal lobe. The mechanism by which beta-amyloid peptide and neurofibrillary tangles cause such damage is incompletely understood. [0078] Soluble oligomeric species of amyloid-β (Aβ) are thought to be key mediators of cognitive dysfunction in Alzheimer’s disease (AD). Neuritic plaques, a hallmark of Alzheimer’s Disease, are accumulations of aggregated, or oligomerized, amyloid beta (Aβ) peptides, including Aβ1-40 (Aβ40) and Aβ1-42 (Aβ42) that are derived from the processing of amyloid precursor protein (APP) by β- and γ-secretases. The vast majority of autosomal familial AD (FAD)-linked mutations are associated with increased levels of Aβ1-42. Aβ production is thought to be activity-dependent, and even in wild type mice addition of soluble Aβ oligomers to hippocampal slices or cultures induces loss of long-term 2 potentiation (LTP), increases long-term depression (LTD) and decreases dendritic spine density. [0079] As is well known in the art, synaptic activity and the change in the strength and number of synapses is central to almost all neurobiological processes, including learning, memory, and neuronal development, which indicia may be monitored in association with the methods disclosed herein. By a “synapse” it is meant the structure on a neuron that permits the neuron to pass an electrical or chemical signal to another cell. By “synaptic plasticity” it is meant the ability of the synapse to change in strength, i.e. to become stronger or weaker, in response to either use or disuse, respectively, of transmission over that synaptic pathway. Such a change in strength is typically evident by one or more of the following structural changes: a change in the number of presynaptic vesicles, a change in the amount of neurotransmitter loaded per vesicle, a change in the number of dendritic spines, and/or a change in the number of neurotransmitter receptors positioned on the postsynaptic neuron. Reductions or enhancements in synaptic plasticity may be observed by assessing the ability of a postsynaptic neuron to evoke a long-term enhancement (“long term potentiation”, LTP) or long-term depression (LTD) in the activity of a presynaptic neuron, and/or by assaying for the subsequent changes in synaptic strength, e.g. by detecting one or more of the above-mentioned structural changes. By “enhanced synaptic plasticity” it is meant greater synaptic strengthening (LTP), more stable synapses and a failure to remove synapses and the spines that carry synapses. By “reduced synaptic plasticity” it is meant enhanced synaptic weakening (LTD), less stable synapses, and fewer spines and synapses. By “synapse loss” it is meant a decrease in the number of synapses, for example, a loss in the connection between two neurons or, in instances in which multiple synapses exist between two neurons, in the loss of one or more of these synapses. Methods for measuring synaptic plasticity in individuals are well known in the art. These include, for example, observing the induction of LTP in neural circuits in awake individuals, e.g. by performing non-invasive stimulation techniques on awake individuals to induce LTP-like long-lasting changes in localized neural activity; mapping plasticity and increased neural circuit activity in individuals, e.g. by using positron emission tomography, functional magnetic resonance imaging, and/or transcranial magnetic stimulation; and by detecting neural plasticity following learning, i.e. improvements in memory, e.g. by assaying retrieval-related brain activity or, e.g., by imaging brain tissue by functional magnetic resonance imaging (fMRI) following repetition priming with familiar and unfamiliar objects. In some aspects of the subject methods, the method further comprises the step of measuring one or more of these effects. [0080] Methods for measuring cognition or vision are also well known in the art, any of which may be used to determine an effective dose. Examples include tests such as cognition tests and IQ test for measuring cognitive ability, e.g. attention and concentration, the ability to learn complex tasks and concepts, memory, information processing, visuospatial function, the ability to produce and understanding language, the ability to solve problems and make decisions, and the ability to perform executive functions; for example, the General Practitioner Assessment of Cognition (GPCOG) test, the Memory Impairment Screen, the Mini Mental State Examination (MMSE), the California Verbal Learning Test, Second Edition, Short Form, for memory, the Delis- Kaplan Executive Functioning System test, and the like. Examples of vision tests include, for example, visual acuity tests, fundoscopy, and the like. [0081] By “cognition” it is meant the mental processes that include attention and concentration, learning complex tasks and concepts, memory (acquiring, retaining, and retrieving new information in the short and/or long term), information processing (dealing with information gathered by the five senses), visuospatial function (visual perception, depth perception, using mental imagery, copying drawings, constructing objects or shapes), producing and understanding language, verbal fluency (word-finding), solving problems, making decisions, and executive functions (planning and prioritizing). Cognition is a faculty for the processing of information, applying knowledge, and changing preferences. By “cognitive plasticity” it is meant the ability to learn, e.g., the ability to learn complex tasks and concepts, analogous to the ability to learn of an organism that is undifferentiated such as a newborn or juvenile, e.g., a human from the time of birth to pre-pubertal age of about 10 years. By “cognitive decline”, it is meant a progressive decrease in cognition, as evidenced by, for example, a decline in one or more of, e.g., attention and concentration, learning complex tasks and concepts, memory (acquiring, retaining, and retrieving new information in the short and/or long term), information processing (dealing with information gathered by the five senses), visuospatial function (visual perception, depth perception, using mental imagery, copying drawings, constructing objects or shapes), producing and understanding language, verbal fluency (word-finding), solving problems, making decisions, and executive functions (planning and prioritizing). By “an impairment in cognitive ability”, “reduced cognitive function”, and “cognitive impairment”, it is meant a reduction in cognitive ability relative to a healthy individual, e.g. an age-matched healthy individual, or relative to the ability of the individual at an earlier point in time, e.g.2 weeks, 1 month, 2 months, 3 months, 6 months, 1 year, 2 years, 5 years, or 10 years or more previously. By “Aβ-associated cognitive decline” and “Aβ-associated cognitive impairment,” it is meant decline or impairment in cognitive ability that is typically associated with the accumulation of Aβ in the nervous system. [0082] Disclosed herein are systems for implementing one or more of the methods or steps of the methods disclosed herein. A computer system includes a central processing unit (CPU, also “processor” and “computer processor” herein), which can be a single core or multi core processor, or a plurality of processors for parallel processing. The system also includes memory (e.g., random-access memory, read-only memory, flash memory), electronic storage unit (e.g., hard disk), communications interface (e.g., network adapter) for communicating with one or more other systems, and peripheral devices, such as cache, other memory, data storage and/or electronic display adapters. The memory, storage unit, interface and peripheral devices are in communication with the CPU through a communications bus, such as a motherboard. The storage unit can be a data storage unit (or data repository) for storing data. The system is operatively coupled to a computer network with the aid of the communications interface. The network can be the Internet, an internet and/or extranet, or an intranet and/or extranet that is in communication with the Internet. The network in some cases is a telecommunication and/or data network. The network can include one or more computer servers, which can enable distributed computing, such as cloud computing. The network in some cases, with the aid of the system, can implement a peer-to-peer network, which may enable devices coupled to the system to behave as a client or a server. [0083] The system is in communication with a processing system. The processing system can be configured to implement the methods disclosed herein. In some examples, the processing system is a nucleic acid sequencing system, such as, for example, a next generation sequencing system (e.g., Illumina sequencer, Ion Torrent sequencer, Pacific Biosciences sequencer). The processing system can be in communication with the system through the network, or by direct (e.g., wired, wireless) connection. The processing system can be configured for analysis, such as nucleic acid sequence analysis. [0084] Methods as described herein can be implemented by way of machine (or computer processor) executable code (or software) stored on an electronic storage location of the system, such as, for example, on the memory or electronic storage unit. During use, the code can be executed by the processor. In some examples, the code can be retrieved from the storage unit and stored on the memory for ready access by the processor. In some situations, the electronic storage unit can be precluded, and machine-executable instructions are stored on memory. [0085] Disclosed herein is a computer-implemented system for calculating a VAF and risk of AD dementia or AD-related pathology. The computer-implemented system may comprise (a) a digital processing device comprising an operating system configured to perform executable instructions and a memory device; and (b) a computer program including instructions executable by the digital processing device, the computer program comprising (i) a first software module configured to receive data pertaining to DNA sequencing; (ii) a second software module configured to relate the sequencing data to generate a VAF; and (iii) a third software module configured to calculate relative risk. [0086] The computer executable logic can work in any computer that may be any of a variety of types of general-purpose computers such as a personal computer, network server, workstation, or other computer platform now or later developed. In some embodiments, a computer program product is described comprising a computer usable medium having the computer executable logic (computer software program, including program code) stored therein. The computer executable logic can be executed by a processor, causing the processor to perform functions described herein. In other embodiments, some functions are implemented primarily in hardware using, for example, a hardware state machine. Implementation of the hardware state machine so as to perform the functions described herein will be apparent to those skilled in the relevant arts. [0087] The program can provide a method of evaluating the presence of clonality in an individual by accessing data that reflects the sequence of the hematopoietic cell population from the individual. In some embodiments, sequence files are trimmed, deduplicated, filtered and aligned to provide a a file of high quality ATAC-seq fragments for all cells a sample. A reference genome can be used for compatibility with a hematopoiesis reference dataset. The fragments file for each sample are then loaded for downstream analysis. [0088] Cell quality control and clustering is performed. Barcodes are called as cells based on fragments per barcode and enrichment of fragments in transcription start sites (TSS) genome wide. For each sample, doublets are predicted and removed based on similarity to computationally simulated doublets. The TileMatrix and GeneScoreMatrix are computed. Dimensionality reduction and clustering can be performed, e.g. tiling the genome into 500 bp windows. After clustering, peaks are determined for each cluster individually to ensure that cell type specific peaks are retained, and merged into a set of disjoint, fixed width peaks used to create a cell by peak matrix. All tracks are identically normalized to correct for variation in sequencing depth and cell quality between different groups of cells. [0089] In one embodiment, the computer executing the computer logic of the invention may also include a digital input device such as a scanner. The digital input device can provide information on a nucleic acid, e.g., mutation levels/quantity. [0090] In some embodiments, the invention provides a computer readable medium comprising a set of instructions recorded thereon to cause a computer to perform the steps of (i) receiving data from one or more nucleic acids detected in a sample; and (ii) diagnosing clonality, response to therapy, or initial diagnosis based on the quantitation. Reports [0091] In some embodiments, providing an evaluation of a subject for a classification, diagnosis, prognosis, theranosis, and/or prediction of an outcome includes generating a written report that includes the artisan’s assessment of the subject’s state of health i.e. a “diagnosis assessment”, of the subject’s prognosis, i.e. a “prognosis assessment”, and/or of possible treatment regimens, i.e. a “treatment assessment”. Thus, a subject method may further include a step of generating or outputting a report providing the results of a diagnosis assessment, a prognosis assessment, or treatment assessment, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible medium (e.g., a report printed on paper or other tangible medium). [0092] A “report,” as described herein, is an electronic or tangible document which includes report elements that provide information of interest relating to a diagnosis assessment, a prognosis assessment, and/or a treatment assessment and its results. A subject report can be completely or partially electronically generated. A subject report includes at least a diagnosis assessment, i.e. a diagnosis as to whether a subject will have a particular clinical responseduring pregnancy, and/or a suggested course of treatment to be followed. A subject report can further include one or more of: 1) information regarding the testing facility; 2) service provider information; 3) subject data; 4) sample data; 5) an assessment report, which can include various information including: a) test data, b) reference values employed, if any. [0093] The report may include information about the testing facility, which information is relevant to the hospital, clinic, or laboratory in which sample gathering and/or data generation was conducted. This information can include one or more details relating to, for example, the name and location of the testing facility, the identity of the lab technician who conducted the assay and/or who entered the input data, the date and time the assay was conducted and/or analyzed, the location where the sample and/or result data is stored, the lot number of the reagents (e.g., kit, etc.) used in the assay, and the like. Report fields with this information can generally be populated using information provided by the user. [0094] The report may include information about the service provider, which may be located outside the healthcare facility at which the user is located, or within the healthcare facility. Examples of such information can include the name and location of the service provider, the name of the reviewer, and where necessary or desired the name of the individual who conducted sample gathering and/or data generation. Report fields with this information can generally be populated using data entered by the user, which can be selected from among pre-scripted selections (e.g., using a drop-down menu). Other service provider information in the report can include contact information for technical information about the result and/or about the interpretive report. [0095] The report may include a subject data section, including subject medical history as well as administrative subject data (that is, data that are not essential to the diagnosis, prognosis, or treatment assessment) such as information to identify the subject (e.g., name, subject date of birth (DOB), gender, mailing and/or residence address, medical record number (MRN), room and/or bed number in a healthcare facility), insurance information, and the like), the name of the subject's physician or other health professional who ordered the susceptibility prediction and, if different from the ordering physician, the name of a staff physician who is responsible for the subject's care (e.g., primary care physician). [0096] The report may include a sample data section, which may provide information about the biological sample analyzed, such as the source of biological sample obtained from the subject (e.g. blood, type of tissue, etc.), how the sample was handled (e.g. storage temperature, preparatory protocols) and the date and time collected. Report fields with this information can generally be populated using data entered by the user, some of which may be provided as pre- scripted selections (e.g., using a drop-down menu). [0097] The report may include an assessment report section, which may include information generated after processing of the data as described herein. The interpretive report can include a prognosis of the likelihood that the patient will develop AD. The interpretive report can include, for example, results of the analysis, methods used to calculate the analysis, and interpretation, i.e. prognosis. The assessment portion of the report can optionally also include a Recommendation(s). [0098] It will also be readily appreciated that the reports can include additional elements or modified elements. For example, where electronic, the report can contain hyperlinks which point to internal or external databases which provide more detailed information about selected elements of the report. For example, the patient data element of the report can include a hyperlink to an electronic patient record, or a site for accessing such a patient record, which patient record is maintained in a confidential database. This latter embodiment may be of interest in an in-hospital system or in-clinic setting. When in electronic format, the report is recorded on a suitable physical medium, such as a computer readable medium, e.g., in a computer memory, zip drive, CD, DVD, etc. [0099] It will be readily appreciated that the report can include all or some of the elements above, with the proviso that the report generally includes at least the elements sufficient to provide the analysis requested by the user (e.g., a diagnosis, a prognosis, or a prediction of responsiveness to a therapy). EXPERIMENTAL [00100] The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the present invention, and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed. Efforts have been made to ensure accuracy with respect to numbers used (e.g. amounts, temperature, etc.) but some experimental errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, molecular weight is weight average molecular weight, temperature is in degrees Centigrade, and pressure is at or near atmospheric. EXAMPLE 1 Clonal Hematopoiesis is Associated with Protection from Alzheimer’s Disease [00101] Clonal hematopoiesis of indeterminate potential (CHIP) is a pre-malignant expansion of mutated blood stem cells that also associates with non-hematological disorders. Here, we tested whether CHIP was associated with Alzheimer’s disease (AD). Surprisingly, we found that CHIP carriers had reduced risk of AD dementia or AD-related pathology in multiple cohorts. The same mutations found in blood were also detected in the microglia-enriched fraction of brain in 7 out of 8 CHIP carriers. Single-cell ATAC-sequencing of brain-derived nuclei in two CHIP carriers revealed that the mutated cells were indistinguishable from microglia and comprised between 42- 77% of the total microglial pool. These results suggest a role for mutant, marrow-derived cells in attenuating risk of AD, possibly by supplementing a failing microglial system during aging. [00102] Given that the common CHIP-associated mutations are known to alter the function of myeloid cells, we hypothesized that CHIP may also be associated with risk of AD. To test this hypothesis, we utilized data from two cohorts within the Trans-omics for Precision Medicine (TOPMed) project, the Framingham Heart Study (FHS) and the Cardiovascular Health Study (CHS). CHIP variants were identified from blood-derived whole genome sequencing data as previously described by Bick et al. Nature (2020) doi:10.1038/s41586-020-2819-2. Participants in CHS were substantially older on average and a higher proportion were female compared to participants in FHS. The FHS subset in TOPMed included some related participants selected for family studies, but was otherwise a random selection of the total cohort. The CHS subset was heavily oversampled for coronary heart disease and stroke, conditions indicative of systemic atherosclerosis (see Materials and Methods). [00103] Vascular dementia, which can mimic AD clinically, is thought to result from reduced blood flow in the brain in part due to atherosclerosis. Given the established association of CHIP with atherosclerotic cardiovascular disease, we excluded participants in both cohorts who had coronary heart disease or stroke. A diagnosis for AD dementia was made based on criteria from the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association for definite, probable, or possible Alzheimer's disease. We excluded anyone with a baseline diagnosis of AD dementia or missing data on incident AD dementia. After these exclusions, there were 2,437 participants in FHS, of whom 92 (3.8%) developed incident AD dementia, and 743 participants in CHS, of whom 166 (22.3%) developed incident AD dementia. Since CHIP is associated with increased risk of mortality, confounding due to survivorship bias may occur when performing association studies for CHIP. To mitigate this possibility, we tested for an association between CHIP and AD dementia using competing risks regression, with death as the competing risk, while also adjusting for age, sex, APOE genotype, study- site (for CHS), and self-reported ancestry. Contrary to our expectations, the presence of CHIP was associated with a lower subdistribution hazard ratio (SHR) for incident AD dementia in both cohorts (SHR 0.69, p=0.13 in CHS; SHR 0.51, p=0.060 in FHS; SHR 0.62, p=0.021 in a fixed-effects meta-analysis of the two cohorts) (FIG.1A, FIG.5). We obtained similar results using Cox proportional hazards regression models or when including family as a clustered variable for FHS. [00104] We next sought confirmation of this surprising inverse association in an independent cohort, the Alzheimer’s Disease Sequencing Project (ADSP), a case-control study for AD with whole exome sequencing (WES) data from brain or blood-derived DNA. APOE genotype is the strongest genetic risk factor for AD, with APOE ε2 alleles conferring protection from disease and APOE ε4 alleles conferring increased risk, as compared to those with APOE ε3ε3. The sample selection strategy for ADSP resulted in cases and controls that were not well-matched for age at WES blood draw for those carrying APOE ε2 or ε4 alleles (see Materials and Methods). Given CHIP’s strong association to age, this selection bias presented a major source of confounding that precluded the analysis of carriers of these alleles. [00105] However, APOE ε3ε3 AD dementia cases and controls were well matched for age, permitting us to test for an association to CHIP in this set. After excluding those with missing information on age at blood draw, a total of 1,446 controls and 1,104 AD dementia cases with blood-derived whole exome sequencing were available for this analysis. In this set, there were no overlapping participants between ADSP and TOPMed. CHIP variants were identified in ADSP using an approach previously described and the prevalence of CHIP was appropriate for the age of the cohort. The sequencing depth in ADSP was higher than for TOPMed, which resulted in greater sensitivity to detect smaller clones. Clone size, which is approximated by the variant allele fraction (VAF), has previously been shown to be an important predictor of risk for blood cancer and cardiovascular outcomes. In order to directly compare outcomes in ADSP to TOPMed, we limited the definition of CHIP carriers to those with VAF>0.08 in this analysis—a cutoff that was chosen because it resulted in a VAF distribution that was nearly identical to TOPMed (FIG.6). We found that CHIP was associated with reduced risk of AD dementia in ADSP (odds ratio [OR] 0.66, p=5.5 x 10^-4) (Figure 1B). In contrast, having VAF≤0.08 had no association to AD dementia (OR 1.25, p=0.23), suggestive of a dose-response relationship between the size of the mutant clone and protection from AD dementia. Indeed, higher VAF was also significantly associated with protection from AD dementia when modeled as a continuous variable. A meta-analysis of ADSP, CHS, and FHS showed that CHIP-carriers had a significant reduction in risk of AD (OR 0.64, p=3.0 x 10^-6) (Figure 1C). In sum, our human genetic association analyses demonstrate that CHIP is associated with protection from AD dementia in multiple cohorts, and that the degree of protection is proportional to the size of the mutant clone. [00106] The neuropathological findings associated with AD, accumulation of amyloid plaques and tau neurofibrillary tangles, can also be found in some people without clinical dementia. A neuritic plaque score developed by the Consortium to Establish a Registry for AD (CERAD) and Braak staging for neurofibrillary tangles are commonly used to assess for these changes at brain autopsy, with an increasing score indicative of more extensive pathology. A subset of participants in ADSP had brain autopsy performed after death, which allowed us to test whether CHIP was associated with AD-related neuropathologic change in those without dementia. Here, the presence of CHIP was associated with lower CERAD neuritic plaque score (OR 0.50, p=3.2 x 10^-3) and Braak stage (OR 0.56, p=0.015) using ordinal logistic regression after adjusting for age, sex and APOE genotype (Figure 1D-E). This shows that CHIP associates with protection from the extent of neuritic plaque and neurofibrillary tangle formation even in the absence of clinical symptoms of dementia. [00107] We next asked whether the protection from AD seen in CHIP carriers was influenced by APOE genotype. In those age 70 or older, APOE genotype was strongly associated with AD dementia risk (p=5.8 x 10^-5 by log-rank test) in those without CHIP. This effect was not seen in CHIP carriers of the same age (p=0.70 by log-rank test), though limited sample size may have prevented us from observing an association for CHIP carriers (Figure 2A). In competing risks regression models, CHIP was associated with protection from AD dementia in those who were APOE ε3ε3 or who carried an APOE ε4 allele, but not in those who had the protective APOE ε2ε2 or APOE ε2ε3 genotypes (Figure 2B). These findings suggest that the mechanism by which CHIP associates with reduced risk of AD dementia might be redundant with the protection conferred through APOE ε2. [00108] We assessed whether the risk of AD dementia varied based on the specific mutated gene. Of the most commonly mutated genes in CHIP, all were associated with protection from AD dementia to a similar degree (Figure 2C). [00109] We wondered whether cells bearing CHIP-associated mutations could be found in brain, a finding that would strengthen the likelihood of a causal association between CHIP and AD risk. We obtained brain DNA-derived WES data from 1,776 persons in ADSP, of whom 1,462 had AD dementia (82.3%), and assessed for the presence of CHIP-associated variants in these samples. We found mutations consistent with CHIP in 17 brain samples, including 15 with AD dementia (Figure 3A). Paired blood DNA was not available for the brain exome samples, so we could not determine whether the mutations we identified were indicative of blood-derived cells in brain. [00110] The microglial pool arises from hematopoietic progenitors during fetal development but is believed to have little contribution from HSC-derived cells in adulthood. Microglia, which are the only hematopoietic cell type in normal human brain, comprise ~1-10% of the total cells in the brain, which varies by brain region. The limit of detection for clonal hematopoiesis by WES is ~4% of cells harboring a mutation in a sample. Therefore, it would be difficult to detect clonal hematopoiesis mutations from unfractionated brain for the vast majority of CHIP carriers using WES. We hypothesized that most CHIP carriers would have the mutations detectable in the brain if examined using more sensitive methods. To test this hypothesis, we obtained tissue samples from the occipital lobe, and in some cases putamen or cerebellum, of 8 donors from the Adult Changes in Thought (ACT) cohort who were known to have CHIP from blood exome sequencing, as well as 1 person without CHIP. All persons were in their 80s and 7 out of 9 were without dementia and had no/low AD neuropathologic change at the time of death. The 8 CHIP carriers had mutations in DNMT3A, TET2, ASXL1, SF3B1, and GNB1 with the highest frequency in DNMT3A (4 out of 8) and TET2 (3 out of 8), which is representative of the relative proportion of these mutations in the general population. In addition, 2 out of the 8 harbored two different CHIP mutations. To determine whether bone marrow derived cells carrying CHIP mutations were present in the brains of these individuals, we digested the frozen brain tissue and isolated intact nuclei, from which we extracted DNA for amplicon sequencing. We detected the same mutations that were present in blood in 6 out of 8 unfractionated brains with variant allele fractions ranging from 0.004 to 0.02 (FIG.7). Of note, the two donors where CHIP variants were not identified in unfractionated brain (ACT1, ACT8) both had AD dementia during life. In contrast, all 6 donors where CHIP variants were found in unfractionated brain were without dementia and free of AD neuropathologic change. [00111] The CHIP variants detected in whole brain DNA could have been derived from residual circulating hematopoietic cells in the vasculature, such as granulocytes or lymphocytes. Alternatively, macrophages or microglia in the brain parenchyma could have been the cell types harboring the mutations. To distinguish between these possibilities, we conceived a strategy to enrich for mononuclear phagocytes from frozen brain tissue. Since the tissue was not viably cryopreserved, isolation of cells based on expression of membrane antigens was not possible. Instead, we used antibodies to nuclear transcription factors to enrich for mononuclear phagocytes, such as macrophages and microglia (Figure 3B). We stained nuclei for the neuronal- specific transcription factor NeuN (RBFOX3) and c-Maf, a transcription factor expressed in phagocytes as well as some neurons and non-hematopoietic glial cells. We then sorted 4 populations based on the presence or absence of these markers (Figure 3B). The CHIP somatic variants were found in the NeuN- c-Maf⁺ population in 7 out 8 brains, with a VAF that ranged from 0.02 to 0.28 (representing 4% to 56% of NeuN- c-Maf⁺ nuclei). In contrast, CHIP somatic variants were not detected in the NeuN+ c-Maf- neuronal population and were absent or at low levels in the other two populations (Figure 3C). The VAF was substantially lower in the NeuN- c-Maf+ nuclei from cerebellum compared to occipital cortex in the three samples where tissue from both regions was available. In sample ACT8, CHIP variants were robustly detected in the NeuN- c- Maf+ population from occipital cortex but not putamen. These results indicate that there is a substantial contribution to the brain mononuclear phagocytic pool from circulating mutated cells, and that there is also regional heterogeneity in the frequency of infiltrating CHIP+ cells in brain. [00112] Our flow cytometric analysis indicated that a prominent myeloid population bearing CHIP mutations was present in the brains of most CHIP carriers. However, it was unknown if the mutated cells were similar to endogenous brain microglia or were instead a distinct myeloid population not normally found in brain. To better understand the phenotype of these mutated cells, we performed single-cell ATAC-sequencing (scATAC-seq) on brain samples from three ACT participants: a brain donor without CHIP (ACT9), one with TET2-mutant CHIP (ACT6), and one with DNMT3A-mutant CHIP (ACT2). For the ACT6 donor, we analyzed tissue from cerebellum and putamen, whereas occipital cortex was assessed for the other two donors. scATAC-seq was performed on unsorted nuclei, as well as sorted NeuN- c-Maf+ nuclei for each sample. After aligning and filtering the scATAC-seq reads, our samples had a median of 12,287 fragments per cell and a median enrichment of fragments in transcription start sites of 9.31, indicating that we recovered high quality scATAC-seq libraries from these archived samples (Figure 8). In total, we recovered high quality scATAC-seq profiles for 38,206 cells. We then aggregated our data with scATAC-seq data from 10 samples (an additional 72,984 cells) from a comprehensive scATAC-seq characterization of the adult human brain. After clustering and dimensionality reduction, we identified 18 clusters encompassing the major brain cell types (Figure 4A-B), including one cluster that contained previously described microglia as well as myeloid cells from each of our samples (cluster 9) (Figure 4B, Figure 9). No other hematopoietic cell types were observed in any human brain samples. [00113] For cells within cluster 9 grouped by sample, inspecting pseudo-bulk ATAC-seq tracks revealed accessible chromatin at the microglia marker genes TMEM119, P2RY12, SALL1, CSF1R, and SIGLEC8 in each of our samples, which was visually similar to the reference microglia. Cells in this cluster also had high accessibility at the AD-associated genes APOE, TREM2, TYROBP, AXL, and MERTK (Figure 4C, Figure 9). As an additional control, we examined reference scATAC-seq profiles of blood monocytes and classical dendritic cells (cDCs) and found that these cells had little to no accessibility at the aforementioned microglia genes. Furthermore, the Cluster 9 tracks in all brain samples had low accessibility at ANPEP (CD13), CXCL2, and ITGAE (CD103), in contrast to monocytes or cDCs (Figure 4C, Figure 9). Finally, we quantified the genome-wide similarity of microglia in each pair of samples by considering the number of differential peaks between each pair for cells within cluster 9. The putamen derived sample showed modest differences from the occipital cortex derived samples but otherwise essentially no differences were observed, and all comparisons were within the range of variation observed when comparing pairs of the Corces 2020 samples (Figure 9). These results indicate that the cells in cluster 9 are indistinguishable from microglia and unlikely to represent contaminating monocytes or dendritic cells. [00114] Having established that the only hematopoietic cell type present in these brains was microglia, we used the scATAC-seq data to evaluate the effectiveness of our flow cytometric method for enrichment of these cells. We compared the proportion of microglia in the sorted samples to those present in the unsorted samples and observed that microglia were enriched 11 to 33-fold in the sorted samples from occipital cortex and cerebellum, but only modestly in the putamen sample (Figure 4D). The percentage of microglia ranged from 7.2% to 25% in the sorted samples, indicating that there were still large numbers of contaminating non-microglial cells in the NeuN- c-Maf+ gate. This suggested that the true fraction of mutated microglia was substantially underestimated by our previous approach using amplicon sequencing of NeuN- c- Maf+ nuclei. To estimate the percentage of mutated microglia more accurately, we first assessed the VAF for the CHIP variant in each unsorted brain sample. Since these are heterozygous mutations, multiplying the VAF by 2 gives an estimate of the percentage of mutated cells in the sample. Since microglia were the only hematopoietic cell type present in these brains, we reasoned that we could divide the percentage of total mutated cells by the percentage of microglia in each unsorted sample to estimate the percentage of mutant microglia. Using this approach, we calculated that 43% of the microglia in ACT2 harbored the DNMT3A mutation, as compared to 28% of circulating cells in the blood. For the ACT6 donor, 77% and 42% of putamen and cerebellar microglia harbored the TET2 mutation, respectively, compared to 28% of circulating blood cells (Figure 4E, Table 14). These results indicate that replacement of endogenous microglia by mutant, marrow-derived cells is widespread in the aging brain. The observation that the proportion of mutated cells is substantially greater in the microglial pool than in the blood also suggests that there is positive selection for the mutant cells in the brain microenvironment. [00115] We show here that, unexpectedly, the presence of CHIP is associated with protection from AD dementia. This effect is seen in multiple cohorts, is not due to survival bias, is seen with several different mutated genes, and is strongest in carriers of APOE ε3ε3 or APOE ε4 alleles. CHIP is also associated with lower levels of amyloid and neurofibrillary pathology in those without dementia, indicating a possible modulating effect of CHIP on the underlying pathophysiology of AD. Consistent with this hypothesis, we also detected substantial infiltration of brain by marrow- derived mutant cells which adopt a microglial-like phenotype. We speculate that the mutations associated with CHIP confer circulating precursor cells with an enhanced ability to engraft in the brain, to differentiate into microglia once engrafted, and/or to clonally expand relative to unmutated cells in the brain microenvironment. These non-mutually exclusive possibilities could provide protection from AD by supplementing the phagocytic capacity of the endogenous microglial system during aging. Alternatively, or in addition, the mutations may alter the functionality of the engrafted myeloid cells in a manner that promotes clearance of pathologic amyloid or tau. Understanding the interplay between CHIP and the aging brain may yield valuable information about the pathogenesis of AD and provide insights into slowing its progression. Materials and Methods Cohort descriptions [00116] Framingham Heart Study. The FHS is a single-site, prospective and population-based study that has followed participants from the town of Framingham, MA to investigate risk factors for cardiovascular diseases. The population of Framingham was almost entirely white at the beginning of the study. The FHS comprises three generations of participants. The first generation (Original cohort/Gen1), followed since 1948, enrolled 5,209 men and women who comprised two- thirds of the adult population then residing in Framingham, MA, USA. Survivors continue to receive biennial examinations. The second generation (Offspring cohort/Gen2), followed since 1971, comprised 5,124 offspring of Gen1 and spouses of the offspring (including 3,514 biological offspring) who attended examinations every 4 to 8 years. The third generation (Gen3), enrolled in 2002, included 4,095 children from the largest offspring families who attended three examinations 4 years apart. All cohorts continue under active surveillance for cardiovascular events, stroke, and dementia. All participants provided written informed consent at each examination. [00117] A total of 4,195 samples were sequenced as part of the Trans-omics for Precision Medicine (TOPMed) project Freeze 6 release as previously described. The selection of participants for sequencing was mostly a random selection of those with available DNA, but also included some related individuals for family studies. After exclusion of participants with coronary heart disease, ischemic stroke, or with missing information on age at blood draw or Alzheimer’s disease (AD) diagnosis, a total of 2,437 persons remained for this analysis. Adjudication for Alzheimer’s phenotypes was done by a committee, comprising at least two neurologists and a neuropsychologist. Multiple types of information were used to evaluate participants with suspected dementia, including neurologic and neuropsychological assessments, a telephone interview with a family member or care giver, medical records, imaging studies, and autopsy data when available. AD was diagnosed when participants met the criteria of the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer's Disease and Related Disorders Association (ADRDA) for definite, probable, or possible Alzheimer's disease. Data for FHS are available in dbGaP. [00118] Cardiovascular Health Study. The CHS is a prospective, multi-ethnic, longitudinal study of risk factors for coronary heart disease and stroke in people aged 65 and older. A total of 2,840 samples were sequenced as part of the Trans-omics for Precision Medicine (TOPMed) project as previously described.The samples selected for whole genome sequencing as part of TOPMed were heavily oversampled for cardiovascular disease cases. After exclusion of participants with coronary heart disease or stroke, or with missing information on age at blood draw or AD diagnosis, a total of 743 persons remained for this analysis. Alzheimer’s disease was diagnosed as probable and possible following the NINCDS-ADRDA criteria in 1997-98 and 2002-03. Data for CHS are available in dbGaP. [00119] Written informed consent was obtained from all human participants by each of the studies that contributed to TOPMed. Each study received institutional certification before deposition in dbGaP, which certified that all relevant institutional ethics committees approved the individual studies and that the genomic and phenotypic data submission was compliant with all relevant ethical regulations. Secondary analysis of the dbGaP data in this manuscript was approved by the Stanford University Institutional Review Board, and this work is compliant with all relevant ethical regulations. [00120] ADSP. The Alzheimer’s Disease Sequencing Project (ADSP) is a collaborative effort of the National Institutes of Aging, the National Human Genome Research Institute, and the Alzheimer’s community to understand the genetic basis of AD.The whole exome sequencing (WES) set of ADSP was a case-control design where cases met NINCDS-ADRDA criteria for possible, probable, or definite AD, had documented age at onset or age at death, and APOE genotyping. A case-control selection strategy was chosen that targeted cases with minimal risk as predicted by known risk factors (age, sex, and APOE) and targeted controls with the least probability of conversion to AD by age 85 years. A total of 5,096 cases and 4,965 controls from 24 cohorts were chosen for WES. As a result of this selection strategy, cases and controls were not well-matched for age, except for carriers of APOE ε3ε3 genotype. Furthermore, 1,776 samples were sequenced from brain, not blood, DNA. We limited our CHIP/AD association analysis to those samples where DNA was derived from blood and where age at blood draw used for sequencing was known. In most cases, the AD diagnosis was made prior to the blood draw, however the diagnosis was usually within 5 years of the time of blood sampling for both prevalent and incident cases. After excluding those without blood DNA or known age at blood draw and further limiting to APOE ε3ε3 carriers, we had 1,104 AD cases and 1,446 controls who were well matched by age. [00121] Written informed consent was obtained from all human participants by each of the studies that contributed to ADSP. Secondary analysis of the dbGaP data in this manuscript was approved by the Partners Healthcare Institutional Review Board, and this work is compliant with all relevant ethical regulations. Data for ADSP is available in dbGaP. [00122] Variant calling and annotation. Whole genome sequencing for TOPMed samples was performed as previously described. FASTQ files were aligned to hg38 for TOPMed WGS and hg19 for ADSP and the resulting BAM files were passed through Mutect/Indelocator (ADSP) or Mutect2 (TOPMed) pipelines to identify putative variants as previously described. Briefly, the Mutect/Mutect2 pipelines excluded variants that had characteristics of common artifacts, such as oxoguanine artifact, end of read artifact, and PCR artifact (strand bias). Common polymorphisms present in germline databases were also excluded. Rare error modes were excluded by using a Panel of Normals compiled from persons without CHIP in the same sequencing centers. Output from the Mutect/Mutect2 pipelines were then annotated for known CHIP variants in 73 genes from a curated whitelist (Table 1). [00123] Statistical analysis plan. TOPMed. We wished to test for an association of AD dementia to CHIP. We hypothesized that CHIP carriers would have increased risk of AD dementia based on prior data that CHIP carriers have more inflammation in innate immune cells and that enhanced inflammasome activation was associated with worsened AD phenotypes in mice. [00124] For the discovery set, we utilized the two cohorts in TOPMed, FHS and CHS. The CHS sample was heavily oversampled for those with cardiovascular diseases, especially coronary heart disease (CHD) and stroke (1,838 out of 2,840 participants had these conditions). CHIP is known to be associated with atherosclerotic cardiovascular disease. As systemic atherosclerosis is a risk factor for vascular dementia, which can mimic AD dementia symptoms, we wished to exclude anyone with these conditions to prevent confounding. To do this, we excluded anyone with an event type of myocardial infarction (MI), stroke, angioplasty, coronary artery bypass surgery, silent MI, or death due to coronary heart disease using CHS event codes and excluded those selected on the basis of CHD, stroke, or “other” sampling group codes. For FHS, we also excluded anyone with codes for coronary heart disease or ischemic stroke. [00125] FHS and CHS are both prospective studies with information on incident AD diagnosis. We therefore utilized regression models to test for an association of CHIP to incident AD dementia in both cohorts. After excluding those without information on AD diagnosis, there were 2,437 persons in FHS and 620 persons in CHS. Other variables included in these models were age at blood draw used for sequencing, APOE genotype, and sex. The results from both cohorts were then meta-analyzed using a fixed-effects meta-analysis. To exclude confounding due to survivorship bias, we performed the analysis using competing risks regression, with death as the competing risk. The R packages survival, meta, and cmprsk were used to perform the Cox models, meta-analysis, and competing risks regression (CRR), respectively. Visual examination of a plot of the Schoenfeld residuals revealed that the proportional hazards assumption was met for each covariate. For FHS, some participants were selected as part of family studies, which could potentially lead to biased estimates in the regression models due to correlated genetic or environmental factors. To control for this possibility, we also included family as a cluster variable in the CRR model for FHS using the R package crrSC and obtained very similar results as with the un-clustered model (Table 4). Therefore, we omitted family as a variable for additional analyses. [00126] ADSP. Having demonstrated a surprising inverse association between CHIP and AD dementia in the discovery set, we wished to replicate the finding. For this, we utilized the ADSP data. As described above, carriers of APOE ε2 or APOE ε4 alleles were selected in such a way that cases and controls were poorly matched for age. Due to this selection bias, carriers of these alleles were excluded from the analysis. However, APOE ε3ε3 carriers were well matched for age, allowing for us to use this set as the replication cohort. We further excluded those without blood as the source for DNA and those without a known age at blood draw used for sequencing. A major difference between ADSP and TOPMed is the use of higher depth whole exome sequencing in ADSP, compared to lower depth whole genome sequencing in TOPMed. In order to perform a power calculation for the replication study in ADSP, we had to ensure the variant allele fraction was comparable between ADSP and TOPMed for two reasons. First, the sensitivity to detect CHIP is linked to the sequencing depth, therefore the prevalence of CHIP was higher in ADSP. Second, the associations for previously studied health outcomes related to CHIP are dependent on clone size, with small clones having less of an effect size. We empirically determined that a cutoff of VAF at 0.08 gave a nearly identical VAF distribution for CHIP clones in ADSP as compared to TOPMed. [00127] After these exclusions, we had 2,550 persons in ADSP for the analysis, of whom 43% were AD cases and 17% were CHIP carriers at a VAF>0.08. We then used the powerMediation package in r to perform a power calculation for varying effect sizes of CHIP at an alpha of 0.1. For an odds ratio of 0.6 (similar to the hazard ratio for CHIP obtained from TOPMed), the power was 1. For an odds ratio of 0.8, the power was 0.96. For an odds ratio of 0.9, the power was 0.50. Thus, we were well-powered for the replication analysis in ADSP. We used logistic regression to assess for the association between CHIP and AD in ADSP, with age at blood draw and sex as other explanatory variables in the model. For privacy concerns, those age 90 or older did not have an exact age available on dbGaP, and were considered to be age 90 for the purposes of this analysis. [00128] We further assessed whether smaller clones were associated with AD dementia in two ways. First, we performed a logistic regression for AD where CHIP status was modeled as a three-factor variable (no CHIP, CHIP with VAF≤0.08, or CHIP with VAF>0.08). Second, we performed a logistic regression for AD dementia where VAF was included as a continuous variable. [00129] We wished to test whether CHIP status was associated to pathologic changes seen in AD in people without clinical dementia symptoms. For a subset of participants in ADSP who died and donated their brains for research, neuritic plaque score based on the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) criteria and Braak stage was assessed. For this analysis, we utilized all APOE genotypes and limited the analysis to those with available age at autopsy. Information on CERAD score was obtained from the National Alzheimer’s Coordinating Center Alzheimer’s Disease Centers (NACC/ADC) and the Adult Changes in Thought (ACT) cohort. Information on Braak stage was available from NACC/ADC, ACT, FHS, and the Genetic Differences cohort. For all cohorts, anyone with a clinical dementia diagnosis was excluded. For NACC/ADC and ACT, we also excluded anyone with mild cognitive impairment. A total of 427 cases had CERAD neuritic plaque scores and 454 cases had Braak stages available for this analysis. We performed ordinal logistic regression for Braak stage using the polr function in the MASS package in R. Explanatory variables included CHIP, age at death, sex, and APOE genotype. The t-values from the ordinal logistic model were used to calculate p-values for each of the covariates using a standard normal distribution. As a separate analysis, we also performed standard logistic regression using Braak stage of IV-VI as the outcome variable. [00130] Nuclei isolation from human postmortem brain tissue. Adult Changes in Thought (ACT) is a longitudinal, community-based observational study of brain aging in participants older than 65 randomly sampled from the Group Health Cooperative (now Kaiser Permanente), a health management organization in King County, Washington. A subset of participants in the study donate their brains for research upon death, and a comprehensive neuropathological exam is performed to assess for AD and related neurodegenerative disease pathologies. For decedents with post-mortem interval of less than 8 hours, a rapid autopsy is performed in which numerous samples from multiple brain regions are taken from one hemisphere and flash frozen in liquid nitrogen. [00131] For this analysis, we obtained occipital cortex samples from 9 ACT brain donors (8 CHIP carriers and 1 non-carrier). Three of these also had a frozen sample from cerebellum available, and 2 had a frozen sample from the putamen. For nuclei isolation, we performed and adapted a protocol. Briefly, around 250 mg of frozen postmortem brain tissue was thawed in 5 mL lysis buffer and transferred to a douncer placed on ice. After 20-30 strokes, the homogenized tissue was transferred to a clear 50 mL ultracentrifuge tube and the volume was adjusted to 12 mL.21 mL of sucrose buffer was added to the bottom of the clear ultracentrifuge tube, to create a concentration gradient with the homogenized tissue solution on top of the sucrose buffer. The tubes were placed in buckets in a SW32Ti swinging rotor (Beckton Dickinson). The samples were ultracentrifuged at 107163.6 RCF for 2.5 hours at 4°C. The supernatant was removed and 500 μL of 1X PBS was added to the pellet and incubated for 20 min on ice. The nuclei were then resuspended and transferred into a microcentrifuge tube. The nuclei were counted using trypan blue dilution and then centrifuged at 500G for 5 min. [00132] Lysis buffer: 0.32M Sucrose, 5 mM CaCl2, 3 mM Mg(Acetate)₂, 0.1 mM EDTA, 10mM Tris-HCl pH8, 1 mM DTT, 0.1%Triton X-100 in H₂0. [00133] Sucrose buffer: 1.8 M Sucrose, 3 mM Mg(Acetate)₂, 1 mM DTT, 10 mM Tris-HCl, pH8 in H20. [00134] Immunostaining and sorting of the nuclei. The nuclei were resuspended at a concentration of 200,000 cells in 50ul of 0.5% BSA in 1x PBS solution and stained for 45 min with Anti-NeuN Antibody Alexa Fluor 488 (EMD Millipore) at a concentration of 1: 400, and Anti-C-MAF antibody PE (BD biosciences) at a concentration of 1: 50. The nuclei were then washed and strained using a 40um strainer. The sorting was done on an Aria II sorter using a 100um nozzle. The nuclei were collected in 0.5% BSA in 1x PBS solution and centrifuged at 500G for 5 min. [00135] DNA extraction, amplification and sequencing. DNA was extracted from the nuclei using the Qiagen QIAmp DNA micro kit. DNA concentration was measured using the Qubit fluorometer. PCR was performed to amplify the region surrounding the mutation of interest (around 300bp) using the Phusion high fidelity master mix (New England Biolabs). The amplified DNA was purified using the Qiagen QIAquick PCR purification kit according to the manufacturer recommendations. Libraries were generated from the pooled amplicons using the Celero DNA- seq library kit (NuGEN). Sequencing of the libraries was performed using MiSeq Nano v2 kits. Sequencing reads were aligned with BWA (http://bio-bwa.sourceforge.net), and variant calling and annotation done with Varscan and Annovar.

scATAC-seq [00136] Sample processing. After nuclei isolation as described above, samples were transposed, single cells were barcoded using 10X Genomics GEMs (Gel Bead in-EMulsions), and libraries were prepared for sequencing according to the commercially available 10X Chromium™ Next GEM Single Cell ATAC Library & Gel Bead Kit v1.1. Paired end sequencing was performed on an Illumina HiSeq 2500. [00137] Analysis pipeline. Fastq files were trimmed, deduplicated, filtered and aligned using the 10X cellranger-atac count pipeline, yielding a file of high quality ATAC-seq fragments for all cells per sample. Reference genome hg19 was used for compatibility with the hematopoiesis reference dataset (described below). The fragments file for each sample was then loaded into ArchR for downstream analysis. [00138] Cell quality control and clustering was performed using the standard ArchR pipeline. Briefly, barcodes were called as cells based on fragments per barcode and enrichment of fragments in transcription start sites (TSS) genome wide. For each sample, doublets were predicted and removed based on similarity to computationally simulated doublets. The TileMatrix and GeneScoreMatrix were computed using default settings. For the GeneScoreMatrix, imputation was performed using the ArchR implementation of MAGIC to aid visualization of the sparse ATAC-seq signals in single cells. Dimensionality reduction and clustering was performed using the TileMatrix, which tiles the genome into 500 bp windows. Although Harmony batch correction is implemented and part of the standard workflow in ArchR, we did not use any batch correction to ensure that any biological differences between the samples would be preserved. After clustering, reproducible peaks were determined for each cluster individually to ensure that cell type specific peaks were retained. Reproducible peaks for each cluster were merged into a set of disjoint, fixed width (500bp) peaks which were used to create the cell by peak matrix. ATAC- seq pseudo-bulk tracks for selected groups of cells were exported from ArchR using the `getGroupBW` function. All tracks were identically normalized using ReadsInTSS, which corrects for variation in sequencing depth and also cell quality between different groups of cells. Specific regions in the genome were visualized using the Integrative Genomics Viewer. [00139] To quantify differences between samples within cluster 9 (the analysis shown in Fig.8C), we used ‘ArchR::getMarkerFeatures’ for every pair of samples in this study, and also every pair of samples in the Corces 2020 data. To control for the different cell numbers within cluster 9 for the different samples, the number of cells considered (per sample) was capped using ‘maxCells=114’, with 114 being the lowest number of cells present across any sample (ACT6 P, Table 13). We then counted the number of peaks passing thresholds FDR < 0.1, abs(log2(fold change)) > 1 for each pairwise comparison. [00140] Reference datasets. To aid in interpretation of cell types from our scATAC-seq data, we incorporated two previously published datasets. For the Corces et. al. brain dataset, original fastq files of all 10 scATAC samples (available under GEO accession no. GSE147672) were aligned to the hg19 reference genome and then processed as described above. For the Satpathy et. al. hematopoiesis dataset, we downloaded fragments files for the 7 samples most relevant to our study, focusing on dendritic cells and monocytes. Accession numbers and sample names of these are: GSM3722015_PBMC_Rep1_fragments.tsv.gz GSM3722076_PBMC_Rep2_fragments.tsv.gz GSM3722075_PBMC_Rep3_fragments.tsv.gz GSM3722077_PBMC_Rep4_fragments.tsv.gz GSM3722039_Dendritic_all_cells_fragments.tsv.gz GSM3722026_Dendritic_Cells_fragments-Reformat.tsv.gz GSM3722027_Monocytes_fragments.tsv.gz [00141] These fragments files were processed in ArchR as described above. After clustering, we identified the predominant dendritic cell cluster and the predominant monocyte cluster based on expression of marker genes and the known sorted sample types. For example, the monocyte cluster contained nearly all cells from the monocyte sample (GSM3722027) as well as cells from the PBMC samples. Normalized bigwig files for each cluster were exported and visualized as described above. Table 1

Table 2 TOPMed Demographics A) Cardiovascular Health Study No AD (n=577) Incident AD (n=166) Mean Age at Blood Draw ± SD 72.8±4.95 74.3±5.01 Female 375 (65.0) 116 (69.9) APOE ε2ε2 or ε2ε3 101 (17.5) 22 (13.2) APOE ε3ε3 340 (58.9) 84 (50.6) APOE ε2ε4 17 (2.9) 9 (5.4) APOE ε3ε4 115 (19.9) 47 (28.3) APOE ε4ε4 4 (0.7) 4 (2.4) CHIP carrier 90 (15.5) 21 (12.7) B) Framingham Heart Study No AD (n=2345) Incident AD (n=92) Mean Age at Blood Draw ± SD 59.6±13.7 80.8±7.54 Female 1312 (55.9) 73 (79.3) APOE ε2ε2 or ε2ε3 303 (12.9) 7 (7.6) APOE ε3ε3 1532 (65.3) 52 (56.5) APOE ε2ε4 44 (1.9) 4 (4.3) A_{POE ε3ε4} ^{430 (18.3) 28 (30.4)} APOE ε4ε4 36 (1.5) 3 (3.3) CHIP carrier 143 (6.1) 9 (9.8) SD—standard deviation Parentheses indicate percent of total of no AD or incident AD groups Table 3 Cox proportional hazards model for risk of AD in TOPMed A) Cardiovascular Health Study CPH model HR 95% CI p-value Age (per year) 1.12 1.08-1.15 2.8 x 10-13 APOE ε2ε2 or ε2ε3 (referent to APOE ε3ε3) 0.85 0.53-1.37 0.51 APOE ε2ε4 (referent to APOE ε3ε3) 2.11 1.04-4.24 0.037 APOE ε3ε4 (referent to APOE ε3ε3) 2.19 1.51-3.19 3.2 x 10-5 APOE ε4ε4 (referent to APOE ε3ε3) 1.63 0.58-4.57 0.35 Females (referent to males) 1.20 0.85-1.69 0.30 Davis site (referent to Bowman Gray) 0.87 0.46-1.64 0.67 Hopkins site (referent to Bowman Gray) 1.76 0.98-3.17 0.060 Pitt site (referent to Bowman Gray) 2.53 1.52-4.22 3.5 x 10-4 Black (referrent to white) 1.54 1.08-2.20 0.018 American Indian (referent to white) 1.43 0.20-10.4 0.72 CHIP carriers (referent to CHIP non-carriers) 0.73 0.46-1.65 0.19 B) Framingham Heart Study CPH model HR 95% CI p-value Age (per year) 1.20 1.17-1.23 <2 x 10-16 APOE ε2ε2 or ε2ε3 (referent to APOE ε3ε3) 0.68 0.31-1.49 0.33 APOE ε2ε4 (referent to APOE ε3ε3) 0.88 0.21-3.64 0.86 APOE ε3ε4 (referent to APOE ε3ε3) 2.22 1.40-3.52 7.5 x 10-4 APOE ε4ε4 (referent to APOE ε3ε3) 5.39 1.64-17.7 5.6 x 10-3 Females (referent to males) 1.66 0.98-2.81 0.062 CHIP carriers (referent to CHIP non-carriers) 0.57 0.28-1.15 0.12 C) Meta-analysis for CHIP

CPH - Cox proportional hazards HR—hazard ratio 95% CI—95 percent confidence interval Table 4. Competing risks regression model for risk of AD in FHS including family as cluster variable SHR 95% CI p-value Age (per year) 1.19 1.16-1.22 2.8 x 10-13 APOE ε2ε2 or ε2ε3 (referent to APOE ε3ε3) 0.61 0.27-1.42 0.25 APOE ε2ε4 (referent to APOE ε3ε3) 0.97 0.20-4.64 0.97 APOE ε3ε4 (referent to APOE ε3ε3) 2.27 0.44-1.45 3.3 x 10-4 APOE ε4ε4 (referent to APOE ε3ε3) 5.60 1.89-16.57 1.9 x 10-3 Females (referent to males) 2.00 1.10-3.62 0.022 CHIP carriers (referrent to non-CHIP carriers) 0.51 0.24-1.05 0.068 Table 5 ADSP Demographics A) ADSP sample Cohort n Controls (APOE ε3ε3) n Cases (APOE ε3ε3) ACT 655 215 ADC 441 516 CHAP 23 1

B) All APOE ε3ε3

SD - standard deviation VAF - variant allele fraction Table 6 Risk of AD in ADSP Logistic regression model for risk of AD

* Those with VAF≤0.08 were considered non-CHIP) OR - odds ratio 95% CI - 95 percent confidence interval Table 7 Risk of AD by VAF in ADSP A) Logistic regression model for risk of AD stratified by VAF cutoff

B) Linear regression model for risk of AD in CHIP carriers using VAF as a continuous variable OR 95% CI p-value

OR - odds ratio 95% CI - 95 percent confidence interval VAF - variant allele fraction Table 8 Neuropathological findings in ADSP controls without dementia or cognitive impairment

C) Ordinal logistic regression model for CERAD score OR 95% CI p-value

D) Ordinal logistic regression model for Braak stage

OR- odds ratio 95% CI - 95 percent confidence interval CERAD - Consortium to establish a registry for Alzheimer's disease Table 9 Risk of AD by APOE genotype in TOPMed A) CRR model for risk of AD in those with APOE ε2ε2 or ε2ε3 CHS SHR 95% CI p-value Age (per year) 0.97 0.90-1.03 0.30 Females (referent to males) 0.69 0.30-1.57 0.38 CHIP (referent to CHIP non-carriers) 1.85 0.61-5.55 0.28 FHS SHR 95% CI p-value Age (per year) 1.18 1.09-1.23 1.5 x 10-6 Females (referent to males) 1.85 0.16-21.5 0.62 CHIP (referent to CHIP non-carriers) 0.82 0.08-8.82 0.87 B) CRR model for risk of AD in those with APOE ε3ε3 CHS SHR 95% CI p-value Age (per year) 1.11 1.07-1.15 2.7 x 10-9 Females (referent to males) 1.38 0.85-2.23 0.19 CHIP (referent to CHIP non-carriers) 0.55 0.27-1.10 0.09 FHS SHR 95% CI p-value Age (per year) 1.23 1.18-1.28 <1 x 10-22 Females (referent to males) 1.66 0.82-3.36 0.16 CHIP (referent to CHIP non-carriers) 0.50 0.22-1.18 0.11 C) CRR model for risk of AD in those with APOE ε2ε4, ε3ε4, or ε4ε4 CHS SHR 95% CI p-value Age (per year) 1.05 1.01-1.11 0.032 Females (referent to males) 1.24 0.65-2.36 0.52 CHIP (referent to CHIP non-carriers) 0.71 0.33-1.54 0.39 FHS SHR 95% CI p-value Age (per year) 1.14 1.10-1.18 1.9 x 10-14 Females (referent to males) 2.07 0.84-5.07 0.11 CHIP (referent to CHIP non-carriers) 0.29 0.03-2.51 0.26 CRR—Competing risks regression SHR—Subdistribution hazard ratio 95% CI—95 percent confidence interval Table 10 Risk of AD by mutated gene A) Logistic regression for risk of AD in TOPMed (CHS and FHS) OR 95% CI p-value Age (per year) 1.16 1.13-1.18 7.6 x 10-41 Females (referent to males) 1.70 1.24-2.34 1.0 x 10-3 FHS (referent to CHS) 0.23 0.17-0.31 2.5 x 10-22 APOE ε2ε2 or ε2ε3 (referent to APOE ε3ε3) 0.86 0.55-1.36 0.52 APOE ε2ε4 (referent to APOE ε3ε3) 1.62 0.76-3.46 0.21 APOE ε3ε4 (referent to APOE ε3ε3) 2.17 1.54-3.04 7.7 x 10-6 APOE ε4ε4 (referent to APOE ε3ε3) 4.60 1.79-11.8 1.5 x 10-3 DNMT3A mutation (referent to CHIP non-carriers) 0.66 0.34-1.29 0.22 TET2 mutation (referent to CHIP non-carriers) 0.56 0.21-1.45 0.24 ASXL1 mutation (referent to CHIP non-carriers) 0.81 0.21-3.13 0.76 SF3B1 mutation (referent to CHIP non-carriers) 0.70 0.08-6.09 0.74 Other mutation (referent to CHIP non-carriers) 0.54 0.20-1.50 0.24 Multiple mutations (referent to CHIP non-carriers) 0.51 1.43-1.84 0.30 B) Logistic regression for risk of AD in ADSP (APOE ε3ε3) OR 95% CI p-value Age (per year) 1.00 0.99-1.01 0.96 Females (referent to males) 0.94 0.80-1.10 0.42 DNMT3A mutation (referent to CHIP non-carriers) 0.75 0.51-1.10 0.14 TET2 mutation (referent to CHIP non-carriers) 0.68 0.42-1.10 0.12 ASXL1 mutation (referent to CHIP non-carriers) 0.55 0.25-1.22 0.14 SF3B1 mutation (referent to CHIP non-carriers) 0.61 0.26-1.44 0.26 Other mutation (referent to CHIP non-carriers) 0.56 0.34-0.90 0.017 Multiple mutations (referent to CHIP non-carriers) 0.73 0.39-1.37 0.33 OR- odds ratio 95% CI - 95 percent confidence interval Table 11 Mutations detected from Whole Exome Sequencing of brain DNA in ADSP ID AD APOE Braak Age Gene Variant Classification Protein Change VAF Alt Ref ADSP_Brain_exome1 1 34 6 82 ASXL1 Frame Shift Insertion p.S1166fs 0.024 5 207 ADSP_Brain_exome2 1 33 3 90 Nonsense Mutation p.Y1692* 0.103 3 26 BCORL1 ADSP_Brain_exome3 1 33 5 90 CBL Missense Mutation p.C404Y 0.04 6 143

ADSP_Brain_exome4 1 33 6 90 Missense Mutation p.R366H 0.086 5 53 DNMT3A ADSP_Brain_exome5 1 34 5 80 GATA3Nonsense Mutation p.C375* 0.038 7 175 ADSP_Brain_exome6 1 34 6 68 NF1 Nonsense Mutation p.S1786* 0.041 4 93 ADSP_Brain_exome7 1 34 6 85 NXF1 Splice Site 0.06 5 79 ADSP_Brain_exome8 0 33 1 90 PRPF8Missense Mutation p.C1594W 0.04 7 168 ADSP_Brain_exome9 1 34 6 83 Missense Mutation p.G870S 0.032 5 150 SETBP1 ADSP_Brain_exome10 1 33 5 85 SRSF2Missense Mutation p.P95H 0.052 4 73 ADSP_Brain_exome11 1 34 5 73 TET2 Frame Shift Deletion p.P656fs 0.081 10 114 ADSP_Brain_exome12 1 34 6 83 TET2 Nonsense Mutation p.Q810* 0.051 7 131 ADSP_Brain_exome13 1 23 5 86 TET2 Missense Mutation p.Q1274P 0.068 4 55 ADSP_Brain_exome14 1 23 5 86 TET2 Nonsense Mutation p.R1465* 0.076 5 61 ADSP_Brain_exome15 1 33 6 90 TET2 Missense Mutation p.R1366H 0.058 6 97 ADSP_Brain_exome16 0 33 0 90 TP53 Missense Mutation p.G266R 0.089 24 247 ADSP_Brain_exome17 1 34 5 ZBTB33 Missense Mutation p.Q59K 0.042 4 92 AD - Alzheimer's (0 - no, 1 - yes) VAF - variant allele fraction Alt - alternate allele read count Ref - reference allele read count

<0.003 <0.003 <0.003 <0.003 AD Alzheimer s (0 no, 1 yes) Sex — 0-male, 1-female VAF — variant allele fraction

Table 13 ATAC-seq cluster counts for each sample

Table 14 Calculation of percentage of mutant microglia in each sample

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Granja, J. M. et al. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat. Genet.53, 403–411 (2021). [00142] The preceding merely illustrates the principles of the invention. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents and equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. The scope of the present invention, therefore, is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of the present invention is embodied by the appended claims.

Claims

THAT WHICH IS CLAIMED IS: 1. A method of determining risk in an individual for developing Alzheimer’s Disease (AD) dementia or AD-related pathology, the method comprising: determining the presence of clonal expansion of hematopoietic cells (CHIP) in the individual, wherein the presence of CHIP reduces risk for developing Alzheimer’s Disease (AD) dementia or AD-related pathology.

2. The method of claim 1, further comprising treating the individual is accordance with the determination of risk.

3. The method of claim 1or claim 2, further comprising the step of providing an assessment of risk to the individual.

4. The method of any of claims 1-3, wherein the the individual is greater than 50 years of age.

5. The method of any of claims 1-4, wherein the presence of clonal expansion is determined by: obtaining a sample of hematopoietic cells from the individual; sequencing nucleic acids from the sample; and determining the presence of somatic mutations; calculating fraction of alleles (VAF) present in the sample of cells that comprise the somatic mutations.

6. The method of claim 5, wherein the hematopoietic cells are peripheral blood cells.

7. The method of claim 5 or claim 6, wherein at least 10⁴ cells are analyzed.

8. The method of any of claims 5-7, wherein sequencing is performed on genomic DNA.

9. The method of any of claims 5-8, wherein sequencing is performed on bulk DNA isolated from the sample of hematopoietic cells.

10. The method of any of claims 5-9, wherein the somatic mutation is present in one or more of DNMT3A, TET2, ASXL1, SF3B1, and GNB1.

11. The method of any of claims 1-10, wherein the individual is determined to have CHIP if the VAF is >0.08.

12. The method of any of claims 1-10, wherein the individual is determined to have CHIP if the VAF is >0.2.

13. The method of any of claims 1-12, further comprising the step of genotyping the individual at the APOE locus.

14. The method of any of claims 1-13, wherein the determination of risk is calculated with a software component configured for analysis of sequencing data.

15. A kit for use in the methods of any of claims 1-14.