A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants.

We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609, p = 7.13 × 10-8) that almost reached genome-wide significance and four additional loci that were suggestively significant. Among these, a novel rare variant (rs145265196) on chromosome 11 had much higher longevity allele frequencies in cases of Ashkenazi Jewish and Southern Italian ancestry compared to cases of other European ancestries. We also correlated EL-associated SNPs with serum proteins to link our findings to potential biological mechanisms that may be related to EL and are under genetic regulation. The findings from the proteomic analyses suggested that longevity-promoting alleles of significant genetic variants either provided EL cases with more youthful molecular profiles compared to controls or provided some form of protection from other illnesses, such as Alzheimer's disease, and disease progressions.

Bayesian Differential Analysis of Cell Type Proportions.

The analysis of cell type proportions in a biological sample should account for the compositional nature of the data but most analyses ignore this characteristic with the risk of producing misleading conclusions. The recent method scCODA appropriately incorporates these constraints by using a Bayesian Multinomial-Dirichlet model that requires a reference cell type to normalize the distribution of all cell types. However, a reference cell type that is stable across biological conditions may not always be available. Here, we present an approach that uses a Bayesian multinomial regression for the analysis of single cell distribution data without the need for a reference cell type. We show an implementation example using the rjags package within the R software.

Multi-modal profiling of peripheral blood cells across the human lifespan reveals distinct immune cell signatures of aging and longevity.

BACKGROUND: Age-related changes in immune cell composition and functionality are associated with multimorbidity and mortality. However, many centenarians delay the onset of aging-related disease suggesting the presence of elite immunity that remains highly functional at extreme old age. METHODS: To identify immune-specific patterns of aging and extreme human longevity, we analyzed novel single cell profiles from the peripheral blood mononuclear cells (PBMCs) of a random sample of 7 centenarians (mean age 106) and publicly available single cell RNA-sequencing (scRNA-seq) datasets that included an additional 7 centenarians as well as 52 people at younger ages (20-89 years). FINDINGS: The analysis confirmed known shifts in the ratio of lymphocytes to myeloid cells, and noncytotoxic to cytotoxic cell distributions with aging, but also identified significant shifts from CD4+ T cell to B cell populations in centenarians suggesting a history of exposure to natural and environmental immunogens. We validated several of these findings using flow cytometry analysis of the same samples. Our transcriptional analysis identified cell type signatures specific to exceptional longevity that included genes with age-related changes (e.g., increased expression of STK17A, a gene known to be involved in DNA damage response) as well as genes expressed uniquely in centenarians' PBMCs (e.g., S100A4, part of the S100 protein family studied in age-related disease and connected to longevity and metabolic regulation). INTERPRETATION: Collectively, these data suggest that centenarians harbor unique, highly functional immune systems that have successfully adapted to a history of insults allowing for the achievement of exceptional longevity. FUNDING: TK, SM, PS, GM, SA, TP are supported by NIH-NIAUH2AG064704 and U19AG023122. MM and PS are supported by NIHNIA Pepper center: P30 AG031679-10. This project is supported by the Flow Cytometry Core Facility at BUSM. FCCF is funded by the NIH Instrumentation grant: S10 OD021587.

Cell Type Diversity Statistic: An Entropy-Based Metric to Compare Overall Cell Type Composition Across Samples.

Changes of cell type composition across samples can carry biological significance and provide insight into disease and other conditions. Single cell transcriptomics has made it possible to study cell type composition at a fine resolution. Most single cell studies investigate compositional changes between samples for each cell type independently, not accounting for the fixed number of cells per sample in sequencing data. Here, we provide a metric of the distribution of cell type proportions in a sample that can be used to compare the overall distribution of cell types across multiple samples and biological conditions. This is the first method to measure overall cell type composition at the single cell level. We use the method to assess compositional changes in peripheral blood mononuclear cells (PBMCs) related to aging and extreme old age using multiple single cell datasets from individuals of four age groups across the human lifespan.

Single cell transcriptomics reveals opioid usage evokes widespread suppression of antiviral gene program.

Chronic opioid usage not only causes addiction behavior through the central nervous system, but also modulates the peripheral immune system. However, how opioid impacts the immune system is still barely characterized systematically. In order to understand the immune modulatory effect of opioids in an unbiased way, here we perform single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells from opioid-dependent individuals and controls to show that chronic opioid usage evokes widespread suppression of antiviral gene program in naive monocytes, as well as in multiple immune cell types upon stimulation with the pathogen component lipopolysaccharide. Furthermore, scRNA-seq reveals the same phenomenon after a short in vitro morphine treatment. These findings indicate that both acute and chronic opioid exposure may be harmful to our immune system by suppressing the antiviral gene program. Our results suggest that further characterization of the immune modulatory effects of opioid is critical to ensure the safety of clinical opioids.