Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different “genetic signatures” of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity.

The persistence of latent HIV-1 remains a major challenge in therapeutic efforts to eradicate infection. We report the capacity for HIV reactivation by a selective small molecule inhibitor of BET family bromodomains, JQ1, a promising therapeutic agent with antioncogenic properties. JQ1 reactivated HIV transcription in models of latent T cell infection and latent monocyte infection. We also tested the effect of exposure to JQ1 to allow recovery of replication-competent HIV from pools of resting CD4(+) T cells isolated from HIV-infected, ART-treated patients. In one of three patients, JQ1 allowed recovery of virus at a frequency above unstimulated conditions. JQ1 potently suppressed T cell proliferation with minimal cytotoxic effect. Transcriptional profiling of T cells with JQ1 showed potent down-regulation of T cell activation genes, including CD3, CD28, and CXCR4, similar to HDAC inhibitors, but JQ1 also showed potent up-regulation of chromatin modification genes, including SIRT1, HDAC6, and multiple lysine demethylases (KDMs). Thus, JQ1 reactivates HIV-1 while suppressing T cell activation genes and up-regulating histone modification genes predicted to favor increased Tat activity. Thus, JQ1 may be useful in studies of potentially novel mechanisms for transcriptional control as well as in translational efforts to identify therapeutic molecules to achieve viral eradication.

At least 10 different genetic human immunodeficiency virus type 1 (HIV-1) subtypes (A-J) are responsible for the AIDS pandemic. Much of the understanding of HIV-1 disease progression derives from studies in the developed world where HIV infection is almost exclusively subtype B. This has led many to question whether the properties and consequences of HIV-1 infection can be generalized across subtypes that afflict the majority of infected persons in the developing world. From 1985 to 1997, a prospective study of registered female sex workers in Senegal tracked the introduction and spread of HIV-1 subtypes A, C, D, and G. In clinical follow-up, the AIDS-free survival curves differed by HIV-1 subtype. Women infected with a non-A subtype were 8 times more likely to develop AIDS than were those infected with subtype A (hazard ratio=8.23; P=. 009), the predominant subtype in the study. These data suggest that HIV-1 subtypes may differ in rates of progression to AIDS.

SummaryBecause people age differently, age is not a sufficient marker of susceptibility to disabilities, morbidities, and mortality. We measured nineteen blood biomarkers that include constituents of standard hematological measures, lipid biomarkers, and markers of inflammation and frailty in 4704 participants of the Long Life Family Study (LLFS), age range 30–110 years, and used an agglomerative algorithm to group LLFS participants into clusters thus yielding 26 different biomarker signatures. To test whether these signatures were associated with differences in biological aging, we correlated them with longitudinal changes in physiological functions and incident risk of cancer, cardiovascular disease, type 2 diabetes, and mortality using longitudinal data collected in the LLFS. Signature 2 was associated with significantly lower mortality, morbidity, and better physical function relative to the most common biomarker signature in LLFS, while nine other signatures were associated with less successful aging, characterized by higher risks for frailty, morbidity, and mortality. The predictive values of seven signatures were replicated in an independent data set from the Framingham Heart Study with comparable significant effects, and an additional three signatures showed consistent effects. This analysis shows that various biomarker signatures exist, and their significant associations with physical function, morbidity, and mortality suggest that these patterns represent differences in biological aging. The signatures show that dysregulation of a single biomarker can change with patterns of other biomarkers, and age‐related changes of individual biomarkers alone do not necessarily indicate disease or functional decline.