This research article investigates how weather conditions influence social media activity by analyzing billions of posts from Facebook and Twitter between 2009 and 2016 alongside meteorological data. The study reveals that both extreme temperatures and precipitation independently lead to increased online engagement, with compounded weather events causing even greater surges. Notably, these effects persist at an individual level and surpass the social media activity seen during major social events like New Year's Eve in New York City. The authors highlight that environmental factors play a significant and often overlooked role in shaping digital social interactions, affecting both weather-related and general online posting. The findings suggest that adverse weather drives people to engage more online, potentially due to reduced offline opportunities. 
https://pubmed.ncbi.nlm.nih.gov/39903688/

This paper by White et al. (2022) discusses ethical considerations and best practices for using large-scale, publicly available datasets, such as the ABCD Study®, for research on American Indian and Alaska Native (AIAN) populations, who have a history of exploitation in mental health research1 .... The authors aim to highlight problematic data use that could perpetuate stereotypes and offer five recommendations, developed with the Cherokee Nation, to promote health research in AIAN communities. The paper critiques a study by Assari (2020) as an example of inappropriate interpretation of ABCD Study® data. The authors identify three main issues: lack of appropriate theoretical rationale, as Assari's model on protective factors was not validated with AIAN communities and ignored existing research; inappropriate interpretation of statistical analyses, including an imbalanced sample size, unreliable mean estimates due to small cell sizes, aggregation of the heterogeneous AIAN/NHPI group, and misinterpreting associations as causal effects; and lack of community engagement or regulatory review. The authors, in partnership with the Cherokee Nation, propose five recommendations for researchers using publicly available AIAN participant data:

(1) Consider heterogeneity of large-scale AIAN samples: Recognize the diverse cultures, histories, languages, and traditions among the 574 federally recognized AIAN nations to avoid overgeneralization.

(2) Prioritize advancement of health and well-being in AIAN communities: Ensure research benefits these communities and consider its impact on public policy and perceptions. Study design should include elements that increase resources and sustainability for tribal research collaborators and build AIAN communities' capacity to engage with publicly available data.

(3) Facilitate community engagement at each stage of the research process: Involve tribal communities early to ensure research relevance, incorporate community knowledge in interpretations, and disseminate findings beyond scientific outlets with bidirectional information sharing.

(4) Consider the impact of social injustices on study variables: Acknowledge the effects of colonization, historical trauma, intergenerational trauma, and discrimination on AIAN mental health and contextualize findings accordingly, especially with biological data as race is not a biological or causal variable.

(5) Engage with tribal research regulatory infrastructure: Comply with tribal regulations (e.g., IRBs, tribal councils) and consult with regulatory bodies for oversight. Future studies should aim to establish coordinated regulatory bodies informed by Indigenous Data Governance (IDG) and Indigenous Data Sovereignty (IDS) principles.
The authors emphasize that both data generators and users share the responsibility for applying these recommendations, along with research reviewers, editors, and publishers. These recommendations are based on principles of community-engaged research and Indigenous Data Sovereignty and Governance, driven by the ethical principle of solidarity. The paper concludes that ethical and culturally appropriate research is crucial to advance understanding of AIAN health and well-being using large-scale publicly available data.

This podcast discusses a recent study that tested how heartbeat perception might be affected within several different mental health conditions. The results suggested that, in depression, anxiety, substance use, and eating disorders, the brain may be less flexible in how it processes signals received from the body. This could be one reason for the emotional difficulties experienced by individuals with these conditions.

​Our lab analyzed questionnaire and blood-based biomarker data collected as part of the Tulsa 1000 study funded by LIBR. We compared three groups of people: (1) those with pure depression, (2) those with comorbid depression + generalized anxiety disorder, and (3) non-depressed/non-anxious individuals. Both depression groups reported higher eating disorder symptoms than the non-depressed group but they did not differ in insulin, adiponectin, or leptin levels. Disordered eating may contribute to daily impairments experienced by people struggling with depression, and could be one future area of intervention.

This is a project from Dr. Stewart's lab using LIBR's Tulsa 1000 dataset.
​We compared people with amphetamine use disorder to those without any substance use disorder (who were allowed to have past depression) on brain activation while they performed a reward anticipation task. ​

IMPORTANCE
​Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable burdens. The etiological factors contributing to TRD are complex and not fully understood.

OBJECTIVE
To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits and explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us (AoU) Research Program.

DESIGN, SETTING, AND PARTICIPANTS
This study was a cohort design with observational data from participants in the AoU Research Program who have both electronic health records and genomic data. Data analysis was performed from March 27 to October 24, 2024.

EXPOSURES
PGS for 61 unique traits from 7 domains.

MAIN OUTCOMES AND MEASURES
Logistic regressions to test if PGSwas associated with treatment-resistant depression (TRD) compared with treatment-responsive major depressive disorder (trMDD). Cox proportional hazard model was used to determine if the progressions from MDD to TRD were associated with PGS.

RESULTS
A total of 292,663 participants (median [IQR] age, 57 (41-69) years; 175 981 female [60.1%]) from the AoU Research Program were included in this analysis. In the discovery set (124 945 participants), 11 of the selected PGS were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia (odds ratio [OR], 1.11; 95%CI, 1.07-1.15) and specific neuroticism (OR, 1.11; 95%CI, 1.07-1.16) traits were associated with increased TRD risk, whereas higher education (OR, 0.88; 95%CI, 0.85-0.91) and intelligence
(OR, 0.91; 95%CI, 0.88-0.94) scores were protective. The associations held across different TRD definitions (meta-analytic R2 >83%) and were consistent across 2 other independent sets within AoU (the whole-genome sequencing Diversity dataset, 104 388, and Microarray dataset, 63 330). Among 28,964 individuals followed up over time, 3,854 developed TRD within a mean of 944 days (95%CI, 883-992 days). All 11 previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD.

CONCLUSIONS AND RELEVANCE
Results of this cohort study suggest that genetic predisposition related to neuroticism, cognitive function, and sleep patterns had a significant association with the development of TRD. These findings underscore the importance of considering psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance understanding of pathways leading to treatment resistance.

Approximately 1/3 of individuals with major depressive disorder (MDD) exhibit low-grade systemic
inflammation based on levels of C-reactive protein (CRP); the American Heart Association defines high risk as a CRP as >3mg/L (1). At the behavioral level, anhedonia appears to be the symptom most closely tied to inflammation (2-4). In healthy participants, inflammatory challenge with low-dose lipopolysaccharide (LPS) - a reliable, safe, and well-validated method of inducing robust peripheral and CNS inflammation (5-8) - transiently increases motivational anhedonia and decreases ventral striatal response to anticipatory reward (9-11).
However, to our knowledge, no study has tested whether depressed individuals with and without systemic inflammation show differential anhedonic responses to an acute inflammatory exposure. Such experimental substantiation would constitute clear evidence of a biological subtype of MDD and corroborate previously proposed mechanistic links between inflammation and anhedonia (2-4). This would also have implications for treatment as it has been proposed that clinical trials of immune-modulating therapies in depression are confounded by a failure to selectively recruit participants with evidence of inflammation (12-15). Here, we present results from a randomized controlled trial (NCT03142919) designed to test whether MDD participants with elevated serum CRP levels (≥3mg/L), as compared to those with non-elevated CRP (≤1.5mg/L), display a greater increase in anhedonic symptoms at the approximate peak of the inflammatory response to LPS, i.e. ~1.5 hours post infusion.

Our study team explored how ibuprofen, a common anti-inflammatory medication, influences brain function related to reward processing. Researchers focused on astrocyte-enriched extracellular vesicles (AEEVs), tiny particles that facilitate communication between brain cells. They discovered that ibuprofen increases the levels of miR-23b-3p, a specific microRNA within AEEVs. Higher levels of this microRNA were associated with reduced inflammation and enhanced activity in the brain's reward centers during anticipation of rewards. These findings suggest that ibuprofen may have potential benefits for brain health by modulating inflammation and influencing reward-related brain activity.​

Cytomegalovirus (CMV) is a common herpesvirus that establishes lifelong latent infections, undergoes periodic reactivation, and may cause disease in vulnerable populations including neonates and the
immunocompromised. CMV has attracted the attention of the psychiatric field because CMV (a) is neurotrophic and may cause neurological disease [1, 2], (b) it can be reactivated by psychological
stress which is linked with the onset and exacerbation of many psychiatric disorders [3, 4], and (c) it can be reactivated by inflammation [4–6], which is linked with multiple psychiatric disorders including mood disorders and schizophrenia [7–11]. Importantly, lytic CMV replication can in turn worsen inflammation
[12, 13], raising the possibility that poorly-controlled CMV infections may be one source of the systemic or neuroinflammation underlying the development of some cases of mental illness [14, 15]. Most of the evidence linking CMV infections to psychiatric disorders is epidemiological [16]. At least 20 studies have reported either a higher frequency of seropositivity to CMV in depressed samples versus controls or a positive correlation between anti-CMV IgG levels and depressive symptoms [16]. In addition, two prospective studies found that CMV seropositivity was associated with an increased risk of subsequent depression [17, 18].

Similarly, a large Swedish cohort study showed that children hospitalized with a CMV infection were 16.6 times more likely to develop a non-affective psychosis in the future [19] and several studies have
linked schizophrenia with CMV infection [20]. We recently published some of the first work linking CMV
seropositivity to neuroimaging abnormalities in the context of major depressive disorder (MDD). In up to three independent samples, we demonstrated that compared with CMV seronegative individuals with MDD, CMV positive individuals with MDD had widespread reductions in gray matter volume, decreased white matter integrity in a tract connecting the frontal and occipital lobes (inferior frontal occipital fasciculus), and reduced functional connectivity between hubs of the sensorimotor and salience networks [21–23]. Leboyer and colleagues had previously reported that CMV antibody levels were inversely associated with hippocampal volume in individuals with bipolar disorder (BD) and schizophrenia [24]. Similarly, Agartz and colleagues recently found that CMV-positive patients with bipolar or schizophrenia spectrum disorders had smaller dentate gyri [25] and reduced total cortical area as compared with CMV-negative patients [26].
​
However, whether CMV is playing a causal role in these neuroimaging abnormalities and if so, whether these findings relate to a heightened inflammatory process, is still unclear. At least in vitro, herpesvirus infections trigger the production of a range of cytokines and chemokines by glial cells [27], but to our knowledge the link between CMV infection and inflammation in the central nervous system (CNS) has never been tested in people with psychiatric disorders.
Here, we investigated in a postmortem sample whether CMV serostatus and serum antibody levels to CMV were associated with the odds of: 1) having a psychiatric disorder, 2) dying by suicide, 3) having higher neuroinflammation (based on a previously performed clustering analysis of immune-related gene expression in the dorsolateral prefrontal cortex [9]), and 4) showing increased microglia activation in the dorsolateral prefrontal cortex (i.e., an increased ratio of non-ramified to ramified microglia). We hypothesized that CMV seropositivity and/or higher CMV antibody levels would be associated with increased odds of 1) diagnosis with a psychiatric disorder, 2), suicide, 3) assignment to the “high” neuroinflammation group, and 4) an increased ratio of nonramified to ramified microglia.