Significance: Humans and our close evolutionary relatives respond differently to a large number of infections. Such differences are thought to result, at least in part, from interspecies differences in immune function. Here, we report on the whole-genome expression of blood leukocytes from four primate species responding to bacterial and viral stimulation. We show that apes mount a markedly stronger early transcriptional response to both viral and bacterial stimulation when compared to African and Asian monkeys. In addition, our findings suggest that apes activate a broader array of defense molecules that may be beneficial for early pathogen killing at the potential cost of increased energy expenditure and tissue damage. Our results provide insight into the evolution of immune responses in primates.

Long COVID is a chronic condition characterized by symptoms such as fatigue, dyspnea, and cognitive impairment that persist or relapse months after an acute infection with the SARS-CoV-2 virus. Many distinct symptoms have been attributed to Long COVID; however, little is known about the potential clustering of these symptoms and risk factors that may predispose patients to certain clusters. In this study, an electronic survey was sent to patients in the UC San Diego Health (UCSDH) system who tested positive for COVID-19, querying if patients were experiencing symptoms consistent with Long COVID. Based on survey results, along with patient demographics reported in the electronic health record (EHR), linear and logistic regression models were used to examine putative risk factors, and exploratory factor analysis was performed to determine symptom clusters. Among 999 survey respondents, increased odds of Long COVID (n = 421; 42%) and greater Long COVID symptom burden were associated with female sex (OR = 1.73, 99% CI: 1.16–2.58; β = 0.48, 0.22–0.75), COVID-19 hospitalization (OR = 4.51, 2.50–8.43; β = 0.48, 0.17–0.78), and poorer pre-COVID self-rated health (OR = 0.75, 0.57–0.97; β = −0.19, −0.32–−0.07). Over one-fifth of Long COVID patients screened positive for depression and/or anxiety, the latter of which was associated with younger age (OR = 0.96, 0.94–0.99). Factor analysis of 16 self-reported symptoms suggested five symptom clusters—gastrointestinal (GI), musculoskeletal (MSK), neurocognitive (NC), airway (AW), and cardiopulmonary (CP), with older age (β = 0.21, 0.11–0.30) and mixed race (β = 0.27, 0.04–0.51) being associated with greater MSK symptom burden. Greater NC symptom burden was associated with increased odds of depression (OR = 5.86, 2.71–13.8) and anxiety (OR = 2.83, 1.36–6.14). These results can inform clinicians in identifying patients at increased risk for Long COVID-related medical issues, particularly neurocognitive symptoms and symptom clusters, as well as informing health systems to manage operational expectations on a population-health level.

Significance: Social adversity is strongly linked to health and fitness outcomes in humans and other social mammals. This observation arises in part through “biological embedding”: persistent, social environment-induced biological changes that may affect immune function. Here we show that low social status in female rhesus macaques leads to a highly proinflammatory response to both bacterial and viral challenge. In addition, we show that past social status also affects gene expression, and that past low status leads to reduced sensitivity to current social conditions. Thus, the first line of defense in the macaque immune system is altered by both current social conditions and a biological memory of past events. Our results provide insight into how social adversity gets under the skin over long time spans.

To compare the effectiveness of 12 weeks of community-based, in-person, group Tai Chi (TC) and Health Education (HAP-E) in improving health and wellbeing in older adults with hypertension and in pr...

Major depressive disorder (MDD) is a highly prevalent, debilitating disorder with a high rate of treatment resistance. One strategy to improve treatment outcomes is to identify patient-specific, pre-intervention factors that can predict treatment success. Neurophysiological measures such as electroencephalography (EEG), which measures the brain’s electrical activity from sensors on the scalp, offer one promising approach for predicting treatment response for psychiatric illnesses, including MDD. In this study, a secondary data analysis was conducted on the publicly available Two Decades Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) database. Logistic regression modeling was used to predict treatment response, defined as at least a 50% improvement on the Beck’s Depression Inventory, in 119 MDD patients receiving repetitive transcranial magnetic stimulation (rTMS). The results show that both age and baseline symptom severity were significant predictors of rTMS treatment response, with older individuals and more severe depression scores associated with decreased odds of a positive treatment response. EEG measures contributed predictive power to these models; however, these improvements in outcome predictability only trended towards statistical significance. These findings provide confirmation of previous demographic and clinical predictors, while pointing to EEG metrics that may provide predictive information in future studies.