Alterations in Activation, Cytotoxic Capacity and Trafficking Profile of Peripheral CD8 T Cells in Young Adult Binge Drinkers

Background: Excess of alcohol consumption is a public health problem and has documented effects on the immune system of humans and animals. Animal and in vitro studies suggest that alcohol abuse changes CD8 T cell (CD8) characteristics, however it remains unknown if the CD8 profile of binge drinkers is different in terms of activation, trafficking and cytotoxic capacity. Aim: To analyze the peripheral CD8 cytotoxic capacity, activation and trafficking phenotypic profile of Mexican young adults with regard to alcohol consumption pattern. Methods: 55 Mexican young adults were stratified as Light (20), Intermediate (18) or Binge drinkers (17) according to their reported alcohol consumption pattern. Blood samples were obtained and hematic biometry and liver enzyme analysis were performed. Peripheral CD8 profile was established by expression of Granzyme B (GB), CD137, CD127, CD69, TLR4, PD1, CCR2, CCR4, CCR5 and CXCR4 by FACS. Data was analyzed by ANOVA, posthoc DMS and Tamhane, and principal component analysis (PCA) with varimax rotation, p\u3c0.05. Results: The Binge drinking group showed increased γGT together with increased expression of CD69 and reduced expression of TLR4, PD1, CCR2 and CXCR4 in peripheral CD8 cells. Other parameters were also specific to Binge drinkers. PCA established 3 factors associated with alcohol consumption: Early Activation represented by CD69 and TLR4 expression in the CD8 population; Effector Activation by CD69 expression in CD8 CD127(+)CD137(+) and CD8 CD25(+) CD137(+); and Trafficking by CXCR4 expression on total CD8 and CD8 GB(+)CXCR4(+), and CCR2 expression on total CD8. Binge drinking pattern showed low expression of Early Activation and Trafficking factors while Light drinking pattern exhibited high expression of Effector Activation factor. Conclusions: Alcohol consumption affects the immune phenotype of CD8 cells since binge drinking pattern was found to be associated with high CD69 and low TLR4, CXCR4 and CCR2 expression, which suggest recent activation, decreased sensitivity to LPS and lower migration capacity in response to chemokines SDF-1 and MCP-1. These results indicate that a binge-drinking pattern of alcohol consumption may induce an altered immune profile that could be related with liver damage and the increased susceptibility to infection reported to this behavior

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Alterations in Activation, Cytotoxic Capacity and Trafficking Profile of Peripheral CD8 T Cells in Young Adult Binge Drinkers.

Excess of alcohol consumption is a public health problem and has documented effects on the immune system of humans and animals. Animal and in vitro studies suggest that alcohol abuse changes CD8 T cell (CD8) characteristics, however it remains unknown if the CD8 profile of binge drinkers is different in terms of activation, trafficking and cytotoxic capacity.To analyze the peripheral CD8 cytotoxic capacity, activation and trafficking phenotypic profile of Mexican young adults with regard to alcohol consumption pattern.55 Mexican young adults were stratified as Light (20), Intermediate (18) or Binge drinkers (17) according to their reported alcohol consumption pattern. Blood samples were obtained and hematic biometry and liver enzyme analysis were performed. Peripheral CD8 profile was established by expression of Granzyme B (GB), CD137, CD127, CD69, TLR4, PD1, CCR2, CCR4, CCR5 and CXCR4 by FACS. Data was analyzed by ANOVA, posthoc DMS and Tamhane, and principal component analysis (PCA) with varimax rotation, p<0.05.The Binge drinking group showed increased γGT together with increased expression of CD69 and reduced expression of TLR4, PD1, CCR2 and CXCR4 in peripheral CD8 cells. Other parameters were also specific to Binge drinkers. PCA established 3 factors associated with alcohol consumption: "Early Activation" represented by CD69 and TLR4 expression in the CD8 population; "Effector Activation" by CD69 expression in CD8 CD127(+)CD137(+) and CD8 CD25(+) CD137(+); and Trafficking by CXCR4 expression on total CD8 and CD8 GB(+)CXCR4(+), and CCR2 expression on total CD8. Binge drinking pattern showed low expression of Early Activation and Trafficking factors while Light drinking pattern exhibited high expression of Effector Activation factor.Alcohol consumption affects the immune phenotype of CD8 cells since binge drinking pattern was found to be associated with high CD69 and low TLR4, CXCR4 and CCR2 expression, which suggest recent activation, decreased sensitivity to LPS and lower migration capacity in response to chemokines SDF-1 and MCP-1. These results indicate that a binge-drinking pattern of alcohol consumption may induce an altered immune profile that could be related with liver damage and the increased susceptibility to infection reported to this behavior

Factorial analysis.

<p><b>A)</b> One way ANOVA stratified by alcohol consumption pattern and 3 specific factors: Early Activation (Upper graph), Effector Activation (Middle graph) and Trafficking (Lower graph) <b>B)</b> Association of the factors in a XYZ surface plot, Z axis Trafficking factor, X axis Early Activation factor and Y axis Effector Activation factor. ^a,b,cIndicates homogeneous groups using DMS contrast where a > b > c. ^A,B,CIndicates homogeneous groups using Tamhane contrast where A > B > C.</p

Alcohol consumption patterns modify the peripheral CD8 profile.

<p><b>A)</b> Flow cytometry analysis of a representative sample of peripheral blood leukocytes; CD8 cells were sorted by forward vs. side scatter pattern (left panel) and the expression of CD3 and CD8 (right panel). Quadrants indicate percentage of CD8. Representative expression of the CD8 profile (left panel): CD25⁺CD127⁺<b>(B)</b> and CD127^-CCR5^high<b>(C)</b>. Scatter plot (right panel) summarizing the distribution (mean ± SD) of indicated CD8 phenotype according to alcohol consumption pattern: CD25⁺CD127⁺<b>(B)</b> and CD127^-CCR5^high<b>(C)</b>. ^a,b,cIndicates homogeneous groups using DMS contrast where a > b > c.</p

Clinical and demographic characteristics of participants according to their drinking pattern.

<p>^a,b,c Indicate homogeneous groups contrast, where a > b > c.</p><p>^¥ Chi-squared Test.</p><p>^& One-way ANOVA DMS post-hoc test.</p><p>^€ One-way ANOVA Tamhane post-hoc test.</p><p>Clinical and demographic characteristics of participants according to their drinking pattern.</p

Measure loadings after varimax rotation of first three components of principal component analysis.

<p>Rotated factor loadings variables of activation, trafficking and cytotoxicity settings were used to conform the components as described in Material and Methods.</p

Alcohol consumption patterns modify the expression of CD69 and TLR4 in peripheral CD8.

<p>Representative FACS histograms for MFI of CD69 (upper panel) and TLR4 (lower panel) in peripheral CD8 population. MFI comparison of control (as FMO) and alcohol consumption groups (left panel). Scatter plot (right panel) summarizing the MFI of CD69 (upper panel) and TLR4 (lower panel) separated by alcohol consumption pattern. FMO: fluorescence minus one. ^a,b,cIndicates homogeneous groups using Tamhane contrast where a > b > c.</p

Immunophenotyping of peripheral T-CD8 participants according to their drinking pattern.

<p>^a,b,c Indicate homogeneous groups contrast, where a > b > c.</p><p>^&One-way ANOVA DMS post-hoc test.</p><p>^€One-way ANOVA Tamhane post-hoc test.</p><p>Immunophenotyping of peripheral T-CD8 participants according to their drinking pattern.</p

Alterations in Activation, Cytotoxic Capacity and Trafficking Profile of Peripheral CD8 T Cells in Young Adult Binge Drinkers

BackgroundExcess of alcohol consumption is a public health problem and has documented effects on the immune system of humans and animals. Animal and in vitro studies suggest that alcohol abuse changes CD8 T cell (CD8) characteristics, however it remains unknown if the CD8 profile of binge drinkers is different in terms of activation, trafficking and cytotoxic capacity.AimTo analyze the peripheral CD8 cytotoxic capacity, activation and trafficking phenotypic profile of Mexican young adults with regard to alcohol consumption pattern.Methods55 Mexican young adults were stratified as Light (20), Intermediate (18) or Binge drinkers (17) according to their reported alcohol consumption pattern. Blood samples were obtained and hematic biometry and liver enzyme analysis were performed. Peripheral CD8 profile was established by expression of Granzyme B (GB), CD137, CD127, CD69, TLR4, PD1, CCR2, CCR4, CCR5 and CXCR4 by FACS. Data was analyzed by ANOVA, posthoc DMS and Tamhane, and principal component analysis (PCA) with varimax rotation, pResultsThe Binge drinking group showed increased γGT together with increased expression of CD69 and reduced expression of TLR4, PD1, CCR2 and CXCR4 in peripheral CD8 cells. Other parameters were also specific to Binge drinkers. PCA established 3 factors associated with alcohol consumption: "Early Activation" represented by CD69 and TLR4 expression in the CD8 population; "Effector Activation" by CD69 expression in CD8 CD127(+)CD137(+) and CD8 CD25(+) CD137(+); and Trafficking by CXCR4 expression on total CD8 and CD8 GB(+)CXCR4(+), and CCR2 expression on total CD8. Binge drinking pattern showed low expression of Early Activation and Trafficking factors while Light drinking pattern exhibited high expression of Effector Activation factor.ConclusionsAlcohol consumption affects the immune phenotype of CD8 cells since binge drinking pattern was found to be associated with high CD69 and low TLR4, CXCR4 and CCR2 expression, which suggest recent activation, decreased sensitivity to LPS and lower migration capacity in response to chemokines SDF-1 and MCP-1. These results indicate that a binge-drinking pattern of alcohol consumption may induce an altered immune profile that could be related with liver damage and the increased susceptibility to infection reported to this behavior