BioVDB: biological vector database for high-throughput gene expression meta-analysis.

High-throughput sequencing has created an exponential increase in the amount of gene expression data, much of which is freely, publicly available in repositories such as NCBI's Gene Expression Omnibus (GEO). Querying this data for patterns such as similarity and distance, however, becomes increasingly challenging as the total amount of data increases. Furthermore, vectorization of the data is commonly required in Artificial Intelligence and Machine Learning (AI/ML) approaches. We present BioVDB, a vector database for storage and analysis of gene expression data, which enhances the potential for integrating biological studies with AI/ML tools. We used a previously developed approach called Automatic Label Extraction (ALE) to extract sample labels from metadata, including age, sex, and tissue/cell-line. BioVDB stores 438,562 samples from eight microarray GEO platforms. We show that it allows for efficient querying of data using similarity search, which can also be useful for identifying and inferring missing labels of samples, and for rapid similarity analysis.

Microglial senescence contributes to female-biased neuroinflammation in the aging mouse hippocampus: implications for Alzheimer's disease.

BACKGROUND: Microglia, the brain's principal immune cells, have been implicated in the pathogenesis of Alzheimer's disease (AD), a condition shown to affect more females than males. Although sex differences in microglial function and transcriptomic programming have been described across development and in disease models of AD, no studies have comprehensively identified the sex divergences that emerge in the aging mouse hippocampus. Further, existing models of AD generally develop pathology (amyloid plaques and tau tangles) early in life and fail to recapitulate the aged brain environment associated with late-onset AD. Here, we examined and compared transcriptomic and translatomic sex effects in young and old murine hippocampal microglia. METHODS: Hippocampal tissue from C57BL6/N and microglial NuTRAP mice of both sexes were collected at young (5-6 month-old [mo]) and old (22-25 mo) ages. Cell sorting and affinity purification techniques were used to isolate the microglial transcriptome and translatome for RNA-sequencing and differential expression analyses. Flow cytometry, qPCR, and imaging approaches were used to confirm the transcriptomic and translatomic findings. RESULTS: There were marginal sex differences identified in the young hippocampal microglia, with most differentially expressed genes (DEGs) restricted to the sex chromosomes. Both sex chromosomally and autosomally encoded sex differences emerged with aging. These sex DEGs identified at old age were primarily female-biased and enriched in senescent and disease-associated microglial signatures. Normalized gene expression values can be accessed through a searchable web interface ( https://neuroepigenomics.omrf.org/ ). Pathway analyses identified upstream regulators induced to a greater extent in females than in males, including inflammatory mediators IFNG, TNF, and IL1B, as well as AD-risk genes TREM2 and APP. CONCLUSIONS: These data suggest that female microglia adopt disease-associated and senescent phenotypes in the aging mouse hippocampus, even in the absence of disease pathology, to a greater extent than males. This sexually divergent microglial phenotype may explain the difference in susceptibility and disease progression in the case of AD pathology. Future studies will need to explore sex differences in microglial heterogeneity in response to AD pathology and determine how sex-specific regulators (i.e., sex chromosomal or hormonal) elicit these sex effects.

Microglial MHC-I induction with aging and Alzheimer's is conserved in mouse models and humans.

Major histocompatibility complex I (MHC-I) CNS cellular localization and function is still being determined after previously being thought to be absent from the brain. MHC-I expression has been reported to increase with brain aging in mouse, rat, and human whole tissue analyses, but the cellular localization was undetermined. Neuronal MHC-I is proposed to regulate developmental synapse elimination and tau pathology in Alzheimer's disease (AD). Here, we report that across newly generated and publicly available ribosomal profiling, cell sorting, and single-cell data, microglia are the primary source of classical and non-classical MHC-I in mice and humans. Translating ribosome affinity purification-qPCR analysis of 3-6- and 18-22-month-old (m.o.) mice revealed significant age-related microglial induction of MHC-I pathway genes B2m, H2-D1, H2-K1, H2-M3, H2-Q6, and Tap1 but not in astrocytes and neurons. Across a timecourse (12-23 m.o.), microglial MHC-I gradually increased until 21 m.o. and then accelerated. MHC-I protein was enriched in microglia and increased with aging. Microglial expression, and absence in astrocytes and neurons, of MHC-I-binding leukocyte immunoglobulin-like (Lilrs) and paired immunoglobin-like type 2 (Pilrs) receptor families could enable cell -autonomous MHC-I signaling and increased with aging in mice and humans. Increased microglial MHC-I, Lilrs, and Pilrs were observed in multiple AD mouse models and human AD data across methods and studies. MHC-I expression correlated with p16INK4A, suggesting an association with cellular senescence. Conserved induction of MHC-I, Lilrs, and Pilrs with aging and AD opens the possibility of cell-autonomous MHC-I signaling to regulate microglial reactivation with aging and neurodegeneration.

Assessing tolerability and physiological responses to 17α-estradiol administration in male rhesus macaques.

17α-estradiol has recently been shown to extend healthspan and lifespan in male mice through multiple mechanisms. These benefits occur in the absence of significant feminization or deleterious effects on reproductive function, which makes 17α-estradiol a candidate for translation into humans. However, human dosing paradigms for the treatment of aging and chronic disease are yet to be established. Therefore, the goals of the current studies were to assess tolerability of 17α-estradiol treatment, in addition to evaluating metabolic and endocrine responses in male rhesus macaque monkeys during a relatively short treatment period. We found that our dosing regimens (0.30 and 0.20 mg/kg/day) were tolerable as evidenced by a lack of GI distress, changes in blood chemistry or complete blood counts, and unaffected vital signs. We also found that the higher dose did elicit mild benefits on metabolic parameters including body mass, adiposity, and glycosylated hemoglobin. However, both of our 17α-estradiol trial doses elicited significant feminization to include testicular atrophy, increased circulating estrogens, and suppressed circulating androgens and gonadotropins. We suspect that the observed level of feminization results from a saturation of the endogenous conjugation enzymes, thereby promoting a greater concentration of unconjugated 17α-estradiol in serum, which has more biological activity. We also surmise that the elevated level of unconjugated 17α-estradiol was subjected to a greater degree of isomerization to 17ß-estradiol, which is aligned with the sevenfold increase in serum 17ß-estradiol in 17α-estradiol treated animals in our first trial. Future studies in monkeys, and certainly humans, would likely benefit from the development and implementation of 17α-estradiol transdermal patches, which are commonly prescribed in humans and would circumvent potential issues with bolus dosing effects.

Microglial MHC-I induction with aging and Alzheimer's is conserved in mouse models and humans.

Major Histocompatibility Complex I (MHC-I) CNS cellular localization and function is still being determined after previously being thought to be absent from the brain. MHC-I expression has been reported to increase with brain aging in mouse, rat, and human whole tissue analyses but the cellular localization was undetermined. Neuronal MHC-I is proposed to regulate developmental synapse elimination and tau pathology in Alzheimer's disease (AD). Here we report that across newly generated and publicly available ribosomal profiling, cell sorting, and single-cell data, microglia are the primary source of classical and non-classical MHC-I in mice and humans. Translating Ribosome Affinity Purification-qPCR analysis of 3-6 and 18-22 month old (m.o.) mice revealed significant age-related microglial induction of MHC-I pathway genes B2m , H2-D1 , H2-K1 , H2-M3 , H2-Q6 , and Tap1 but not in astrocytes and neurons. Across a timecourse (12-23 m.o.), microglial MHC-I gradually increased until 21 m.o. and then accelerated. MHC-I protein was enriched in microglia and increased with aging. Microglial expression, and absence in astrocytes and neurons, of MHC-I binding Leukocyte Immunoglobulin-like (Lilrs) and Paired immunoglobin-like type 2 (Pilrs) receptor families could enable cell-autonomous MHC-I signaling and increased with aging in mice and humans. Increased microglial MHC-I, Lilrs, and Pilrs were observed in multiple AD mouse models and human AD data across methods and studies. MHC-I expression correlated with p16INK4A , suggesting an association with cellular senescence. Conserved induction of MHC-I, Lilrs, and Pilrs with aging and AD opens the possibility of cell-autonomous MHC-I signaling to regulate microglial reactivation with aging and neurodegeneration.

Microglial senescence contributes to female-biased neuroinflammation in the aging mouse hippocampus: implications for Alzheimer's disease.

Background: Microglia, the brain's principal immune cells, have been implicated in the pathogenesis of Alzheimer's disease (AD), a condition shown to affect more females than males. Although sex differences in microglial function and transcriptomic programming have been described across development and in disease models of AD, no studies have comprehensively identified the sex divergences that emerge in the aging mouse hippocampus. Further, existing models of AD generally develop pathology (amyloid plaques and tau tangles) early in life and fail to recapitulate the aged brain environment associated with late-onset AD. Here, we examined and compared transcriptomic and translatomic sex effects in young and old murine hippocampal microglia. Methods: Hippocampal tissue from C57BL6/N and microglial NuTRAP mice of both sexes were collected at young (5-6 month-old [mo]) and old (22-25 mo) ages. Cell sorting and affinity purification techniques were used to isolate the microglial transcriptome and translatome for RNA-sequencing and differential expression analyses. Flow cytometry, qPCR, and imaging approaches were used to confirm the transcriptomic and translatomic findings. Results: There were marginal sex differences identified in the young hippocampal microglia, with most differentially expressed genes (DEGs) restricted to the sex chromosomes. Both sex chromosomally-and autosomally-encoded sex differences emerged with aging. These sex DEGs identified at old age were primarily female-biased and enriched in senescent and disease-associated microglial signatures. Normalized gene expression values can be accessed through a searchable web interface ( https://neuroepigenomics.omrf.org/ ). Pathway analyses identified upstream regulators induced to a greater extent in females than in males, including inflammatory mediators IFNG, TNF, and IL1B, as well as AD-risk genes TREM2 and APP. Conclusions: These data suggest that female microglia adopt disease-associated and senescent phenotypes in the aging mouse hippocampus, even in the absence of disease pathology, to a greater extent than males. This sexually divergent microglial phenotype may explain the difference in susceptibility and disease progression in the case of AD pathology. Future studies will need to explore sex differences in microglial heterogeneity in response to AD pathology and determine how sex-specific regulators (i.e., sex chromosomal or hormonal) elicit these sex effects.

Methylation Array Signals are Predictive of Chronological Age Without Bisulfite Conversion.

DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. Here, we demonstrate how another hallmark of aging, genomic instability, influences methylation measurements in both bisulfite sequencing and methylation arrays. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.

Many chronological aging clocks can be found throughout the epigenome: Implications for quantifying biological aging.

Epigenetic alterations are a hallmark of aging and age-related diseases. Computational models using DNA methylation data can create "epigenetic clocks" which are proposed to reflect "biological" aging. Thus, it is important to understand the relationship between predictive clock sites and aging biology. To do this, we examined over 450,000 methylation sites from 9,699 samples. We found ~20% of the measured genomic cytosines can be used to make many different epigenetic clocks whose age prediction performance surpasses that of telomere length. Of these predictive sites, the average methylation change over a lifetime was small (~1.5%) and these sites were under-represented in canonical regions of epigenetic regulation. There was only a weak association between "accelerated" epigenetic aging and disease. We also compare tissue-specific and pan-tissue clock performance. This is critical to applying clocks both to new sample sets in basic research, as well as understanding if clinically available tissues will be feasible samples to evaluate "epigenetic aging" in unavailable tissues (e.g., brain). Despite the reproducible and accurate age predictions from DNA methylation data, these findings suggest they may have limited utility as currently designed in understanding the molecular biology of aging and may not be suitable as surrogate endpoints in studies of anti-aging interventions. Purpose-built clocks for specific tissues age ranges or phenotypes may perform better for their specific purpose. However, if purpose-built clocks are necessary for meaningful predictions, then the utility of clocks and their application in the field needs to be considered in that context.

Sexually divergent DNA methylation patterns with hippocampal aging.

DNA methylation is a central regulator of genome function, and altered methylation patterns are indicative of biological aging and mortality. Age-related cellular, biochemical, and molecular changes in the hippocampus lead to cognitive impairments and greater vulnerability to neurodegenerative disease that varies between the sexes. The role of hippocampal epigenomic changes with aging in these processes is unknown as no genome-wide analyses of age-related methylation changes have considered the factor of sex in a controlled animal model. High-depth, genome-wide bisulfite sequencing of young (3 month) and old (24 month) male and female mouse hippocampus revealed that while total genomic methylation amounts did not change with aging, specific sites in CG and non-CG (CH) contexts demonstrated age-related increases or decreases in methylation that were predominantly sexually divergent. Differential methylation with age for both CG and CH sites was enriched in intergenic and intronic regions and under-represented in promoters, CG islands, and specific enhancer regions in both sexes, suggesting that certain genomic elements are especially labile with aging, even if the exact genomic loci altered are predominantly sex-specific. Lifelong sex differences in autosomal methylation at CG and CH sites were also observed. The lack of genome-wide hypomethylation, sexually divergent aging response, and autosomal sex differences at CG sites was confirmed in human data. These data reveal sex as a previously unappreciated central factor of hippocampal epigenomic changes with aging. In total, these data demonstrate an intricate regulation of DNA methylation with aging by sex, cytosine context, genomic location, and methylation level.