Evaluation of aldehyde dehydrogenase 1 promoter polymorphisms identified in human populations

BACKGROUND: Cytosolic aldehyde dehydrogenase, or ALDH1A1, functions in ethanol detoxification, metabolism of neurotransmitters, and synthesis of retinoic acid. Because the promoter region of a gene can influence gene expression, the ALDH1A1 promoter regions were studied to identify polymorphism, to assess their functional significance, and to determine whether they were associated with a risk for developing alcoholism. METHODS: Sequence analysis was performed in the promoter region by using Asian, Caucasian, and African American subjects. The resulting polymorphisms were assessed for frequency in Asian, Caucasian, Jewish, and African American populations and tested for associations with alcohol dependence in Asian and African American populations of alcoholics and controls. The functional significance of each polymorphism was determined through in vitro expression analysis by using HeLa and HepG2 cells. RESULTS: Two polymorphisms, a 17 base pair (bp) deletion (-416/-432) and a 3 bp insertion (-524), were discovered in the ALDH1A1 promoter region: ALDH1A1*2 and ALDH1A1*3, respectively. ALDH1A1*2 was observed at frequencies of 0.035, 0.023, 0.023, and 0.012 in the Asian, Caucasian, Jewish, and African American populations, respectively. ALDH1A1*3 was observed only in the African American population, at a frequency of 0.029. By using HeLa and HepG2 cells for in vitro expression, the activity of the luciferase reporter gene was significantly decreased after transient transfection of ALDH1A1*3-luciferase compared with the wild-type construct ALDH1A1*1-luciferase. In an African American population, a trend for higher frequencies of the ALDH1A1*2 and ALDH1A1*3 alleles was observed in a population of alcoholics (p = 0.03 and f = 0.12, respectively) compared with the control population. CONCLUSIONS: ALDH1A1*2 and ALDH1A1*3 may influence ALDH1A1 gene expression. Both ALDH1A1*2 and ALDH1A1*3 produce a trend in an African American population that may be indicative of an association with alcoholism; however, more samples are required to validate this observation. The underlying mechanisms contributing to these trends are still unknown

Long-lived T follicular helper cells retain plasticity and help sustain humoral immunity

CD4; +; memory T cells play an important role in protective immunity and are a key target in vaccine development. Many studies have focused on T central memory (T; cm; ) cells, whereas the existence and functional significance of long-lived T follicular helper (T; fh; ) cells are controversial. Here, we show that T; fh; cells are highly susceptible to NAD-induced cell death (NICD) during isolation from tissues, leading to their underrepresentation in prior studies. NICD blockade reveals the persistence of abundant T; fh; cells with high expression of hallmark T; fh; markers to at least 400 days after infection, by which time T; cm; cells are no longer found. Using single-cell RNA-seq, we demonstrate that long-lived T; fh; cells are transcriptionally distinct from T; cm; cells, maintain stemness and self-renewal gene expression, and, in contrast to T; cm; cells, are multipotent after recall. At the protein level, we show that folate receptor 4 (FR4) robustly discriminates long-lived T; fh; cells from T; cm; cells. Unexpectedly, long-lived T; fh; cells concurrently express a distinct glycolytic signature similar to trained immune cells, including elevated expression of mTOR-, HIF-1-, and cAMP-regulated genes. Late disruption of glycolysis/ICOS signaling leads to T; fh; cell depletion concomitant with decreased splenic plasma cells and circulating antibody titers, demonstrating both unique homeostatic regulation of T; fh; and their sustained function during the memory phase of the immune response. These results highlight the metabolic heterogeneity underlying distinct long-lived T cell subsets and establish T; fh; cells as an attractive target for the induction of durable adaptive immunity

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip

Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events

Developing a Series of AI Challenges for the United States Department of the Air Force

Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have influenced organizations such as the United States Department of the Air Force (DAF). The DAF-MIT AI Accelerator is an initiative between the DAF and MIT to bridge the gap between AI researchers and DAF mission requirements. Several projects supported by the DAF-MIT AI Accelerator are developing public challenge problems that address numerous Federal AI research priorities. These challenges target priorities by making large, AI-ready datasets publicly available, incentivizing open-source solutions, and creating a demand signal for dual use technologies that can stimulate further research. In this article, we describe these public challenges being developed and how their application contributes to scientific advances

Biased Saccadic Responses to Emotional Stimuli in Anxiety: An Antisaccade Study.

Research suggests that anxiety is maintained by an attentional bias to threat, and a growing base of evidence suggests that anxiety may additionally be associated with the deficient attentional processing of positive stimuli. The present study sought to examine whether such anxiety-linked attentional biases were associated with either stimulus driven or attentional control mechanisms of attentional selectivity. High and low trait anxious participants completed an emotional variant of an antisaccade task, in which they were required to prosaccade towards, or antisaccade away from a positive, neutral or threat stimulus, while eye movements were recorded. While low anxious participants were found to be slower to saccade in response to positive stimuli, irrespectively of whether a pro- or antisaccade was required, such a bias was absent in high anxious individuals. Analysis of erroneous antisaccades further revealed at trend level, that anxiety was associated with reduced peak velocity in response to threat. The findings suggest that anxiety is associated with the aberrant processing of positive stimuli, and greater compensatory efforts in the inhibition of threat. The findings further highlight the relevance of considering saccade peak velocity in the assessment of anxiety-linked attentional processing