Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain.

The mammalian brain is composed of diverse, specialized cell populations. To systematically ascertain and learn from these cellular specializations, we used Drop-seq to profile RNA expression in 690,000 individual cells sampled from 9 regions of the adult mouse brain. We identified 565 transcriptionally distinct groups of cells using computational approaches developed to distinguish biological from technical signals. Cross-region analysis of these 565 cell populations revealed features of brain organization, including a gene-expression module for synthesizing axonal and presynaptic components, patterns in the co-deployment of voltage-gated ion channels, functional distinctions among the cells of the vasculature and specialization of glutamatergic neurons across cortical regions. Systematic neuronal classifications for two complex basal ganglia nuclei and the striatum revealed a rare population of spiny projection neurons. This adult mouse brain cell atlas, accessible through interactive online software (DropViz), serves as a reference for development, disease, and evolution.

CSMD1 regulates brain complement activity and circuit development.

Complement proteins facilitate synaptic elimination during neurodevelopmental pruning, but neural complement regulation is not well understood. CUB and Sushi Multiple Domains 1 (CSMD1) can regulate complement activity in vitro, is expressed in the brain, and is associated with increased schizophrenia risk. Beyond this, little is known about CSMD1 including whether it regulates complement activity in the brain or otherwise plays a role in neurodevelopment. We used biochemical, immunohistochemical, and proteomic techniques to examine the regional, cellular, and subcellular distribution as well as protein interactions of CSMD1 in the brain. To evaluate whether CSMD1 is involved in complement-mediated synapse elimination, we examined Csmd1-knockout mice and CSMD1-knockout human stem cell-derived neurons. We interrogated synapse and circuit development of the mouse visual thalamus, a process that involves complement pathway activity. We also quantified complement deposition on synapses in mouse visual thalamus and on cultured human neurons. Finally, we assessed uptake of synaptosomes by cultured microglia. We found that CSMD1 is present at synapses and interacts with complement proteins in the brain. Mice lacking Csmd1 displayed increased levels of complement component C3, an increased colocalization of C3 with presynaptic terminals, fewer retinogeniculate synapses, and aberrant segregation of eye-specific retinal inputs to the visual thalamus during the critical period of complement-dependent refinement of this circuit. Loss of CSMD1 in vivo enhanced synaptosome engulfment by microglia in vitro, and this effect was dependent on activity of the microglial complement receptor, CR3. Finally, human stem cell-derived neurons lacking CSMD1 were more vulnerable to complement deposition. These data suggest that CSMD1 can function as a regulator of complement-mediated synapse elimination in the brain during development.

Returning Individual Research Results from Digital Phenotyping in Psychiatry.

Psychiatry is rapidly adopting digital phenotyping and artificial intelligence/machine learning tools to study mental illness based on tracking participants' locations, online activity, phone and text message usage, heart rate, sleep, physical activity, and more. Existing ethical frameworks for return of individual research results (IRRs) are inadequate to guide researchers for when, if, and how to return this unprecedented number of potentially sensitive results about each participant's real-world behavior. To address this gap, we convened an interdisciplinary expert working group, supported by a National Institute of Mental Health grant. Building on established guidelines and the emerging norm of returning results in participant-centered research, we present a novel framework specific to the ethical, legal, and social implications of returning IRRs in digital phenotyping research. Our framework offers researchers, clinicians, and Institutional Review Boards (IRBs) urgently needed guidance, and the principles developed here in the context of psychiatry will be readily adaptable to other therapeutic areas.

Schizophrenia risk from complex variation of complement component 4.

Schizophrenia is a heritable brain illness with unknown pathogenic mechanisms. Schizophrenia's strongest genetic association at a population level involves variation in the major histocompatibility complex (MHC) locus, but the genes and molecular mechanisms accounting for this have been challenging to identify. Here we show that this association arises in part from many structurally diverse alleles of the complement component 4 (C4) genes. We found that these alleles generated widely varying levels of C4A and C4B expression in the brain, with each common C4 allele associating with schizophrenia in proportion to its tendency to generate greater expression of C4A. Human C4 protein localized to neuronal synapses, dendrites, axons, and cell bodies. In mice, C4 mediated synapse elimination during postnatal development. These results implicate excessive complement activity in the development of schizophrenia and may help explain the reduced numbers of synapses in the brains of individuals with schizophrenia.

Incidental Findings from Deep Phenotyping Research in Psychiatry: Legal and Ethical Considerations.

Substantial advancement in the diagnosis and treatment of psychiatric disorders may come from assembling diverse data streams from clinical notes, neuroimaging, genetics, and real-time digital footprints from smartphones and wearable devices. This is called "deep phenotyping" and often involves machine learning. We argue that incidental findings arising in deep phenotyping research have certain special, morally and legally salient features: They are specific, actionable, numerous, and probabilistic. We consider ethical and legal implications of these features and propose a practical ethics strategy for managing them.

Gender-specificity of resilience in major depressive disorder.

INTRODUCTION: The major stressors associated with the COVID-19 pandemic provide an opportunity to understand the extent to which protective factors against depression may exhibit gender-specificity. METHOD: This study examined responses from multiple waves of a 50 states non-probability internet survey conducted between May 2020 and January 2021. Participants completed the PHQ-9 as a measure of depression, as well as items characterizing social supports. We used logistic regression models with population reweighting to examine association between absence of even mild depressive symptoms and sociodemographic features and social supports, with interaction terms and stratification used to investigate sex-specificity. RESULTS: Among 73,917 survey respondents, 31,199 (42.2%) reported absence of mild or greater depression-11,011/23,682 males (46.5%) and 20,188/50,235 (40.2%) females. In a regression model, features associated with greater likelihood of depression-resistance included at least weekly attendance of religious services (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04-1.16) and greater trust in others (OR: 1.04 for a 2-unit increase, 95% CI: 1.02-1.06), along with level of social support measured as number of social ties available who could provide care (OR: 1.05, 95% CI: 1.02-1.07), talk to them (OR: 1.10, 95% CI: 1.07-1.12), and help with employment (OR: 1.06, 95% CI: 1.04-1.08). The first two features showed significant interaction with gender (p < .0001), with markedly greater protective effects among women. CONCLUSION: Aspects of social support are associated with diminished risk of major depressive symptoms, with greater effects of religious service attendance and trust in others observed among women than men.

Patient Requests for Off-Label Bioprediction of Dementia.

In 2012, the FDA approved for the differential diagnosis of Alzheimer's disease a brain-imaging technology, Amyvid-PET (aka florbetapir-PET), capable of non-invasively estimating the burden of amyloid plaques; this approval for one indication renders the technology a candidate for off-label use for another indication according to a physician's judgment. What should a physician do if an educated, pro-active, and concerned patient requests off-label use of Amyvid-PET to help her estimate the likelihood that her mild memory complaints are "just normal aging" or are likely to profoundly worsen? I consider reasons that a physician might justify denial of such a request, including concerns of safety, uncertain benefit, and fair resource allocation, but cautiously conclude that there may be certain cases where off-label bioprediction would be permissible.

Therapeutic implications for striatal-enriched protein tyrosine phosphatase (STEP) in neuropsychiatric disorders.

Striatal-enriched protein tyrosine phosphatase (STEP) is a brain-specific phosphatase that modulates key signaling molecules involved in synaptic plasticity and neuronal function. Targets include extracellular-regulated kinase 1 and 2 (ERK1/2), stress-activated protein kinase p38 (p38), the Src family tyrosine kinase Fyn, N-methyl-D-aspartate receptors (NMDARs), and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs). STEP-mediated dephosphorylation of ERK1/2, p38, and Fyn leads to inactivation of these enzymes, whereas STEP-mediated dephosphorylation of surface NMDARs and AMPARs promotes their endocytosis. Accordingly, the current model of STEP function posits that it opposes long-term potentiation and promotes long-term depression. Phosphorylation, cleavage, dimerization, ubiquitination, and local translation all converge to maintain an appropriate balance of STEP in the central nervous system. Accumulating evidence over the past decade indicates that STEP dysregulation contributes to the pathophysiology of several neuropsychiatric disorders, including Alzheimer's disease, schizophrenia, fragile X syndrome, epileptogenesis, alcohol-induced memory loss, Huntington's disease, drug abuse, stroke/ischemia, and inflammatory pain. This comprehensive review discusses STEP expression and regulation and highlights how disrupted STEP function contributes to the pathophysiology of diverse neuropsychiatric disorders.

Human-derived monoclonal autoantibodies as interrogators of cellular proteotypes in the brain.

A major aim of neuroscience is to identify and model the functional properties of neural cells whose dysfunction underlie neuropsychiatric illness. In this article, we propose that human-derived monoclonal autoantibodies (HD-mAbs) are well positioned to selectively target and manipulate neural subpopulations as defined by their protein expression; that is, cellular proteotypes. Recent technical advances allow for efficient cloning of autoantibodies from neuropsychiatric patients. These HD-mAbs can be introduced into animal models to gain biological and pathobiological insights about neural proteotypes of interest. Protein engineering can be used to modify, enhance, silence, or confer new functional properties to native HD-mAbs, thereby enhancing their versatility. Finally, we discuss the challenges and limitations confronting HD-mAbs as experimental research tools for neuroscience.

Pharmacogenomic Clinical Support Tools for the Treatment of Depression.

OBJECTIVE: In this review, the authors update the 2018 position statement of the American Psychiatric Association Council of Research Workgroup on Biomarkers and Novel Treatments on pharmacogenomic (PGx) tools for treatment selection in depression. METHODS: The literature was reviewed for new clinical trials and meta-analyses, published from 2017 to 2022, of studies using PGx tools for treatment selection in depression. The blinding and control conditions, as well as primary and secondary outcomes and post hoc analyses, were summarized. RESULTS: Eleven new clinical trials and five meta-analyses were identified; all studies had primary outcome measures related to speed or efficacy of treatment response. Three trials (27%) demonstrated efficacy on the primary outcome measure with statistical significance; the three studies used different PGx tools; one study was open-label and the other two were small single-blind trials. Five trials (45%) did not detect efficacy with statistical significance on either primary or secondary outcome measures. Only one trial (9%) used adverse events as a primary outcome measure. All studies had significant limitations; for example, none adopted a fully blinded study design, only two studies attempted to blind the treating clinician, and none incorporated measures to estimate the effectiveness of the blinds or the influence of lack of blinding on the study results. CONCLUSIONS: The addition of these new data do not alter the recommendations of the 2018 report, or the advice of the U.S. Food and Drug Administration, that the evidence does not support the use of currently available combinatorial PGx tools for treatment selection in major depressive disorder. Priority efforts for future studies and the development and testing of effective tools include fully blinded study designs, inclusion of promising genetic variants not currently included in any commercially available tests, and investigation of other uses of pharmacogenomics, such as estimating the likelihood of rare adverse drug effects, rather than increasing the speed or magnitude of drug response.

Trust in Physicians and Hospitals During the COVID-19 Pandemic in a 50-State Survey of US Adults.

Importance: Trust in physicians and hospitals has been associated with achieving public health goals, but the increasing politicization of public health policies during the COVID-19 pandemic may have adversely affected such trust. Objective: To characterize changes in US adults' trust in physicians and hospitals over the course of the COVID-19 pandemic and the association between this trust and health-related behaviors. Design, Setting, and Participants: This survey study uses data from 24 waves of a nonprobability internet survey conducted between April 1, 2020, and January 31, 2024, among 443 455 unique respondents aged 18 years or older residing in the US, with state-level representative quotas for race and ethnicity, age, and gender. Main Outcome and Measure: Self-report of trust in physicians and hospitals; self-report of SARS-CoV-2 and influenza vaccination and booster status. Survey-weighted regression models were applied to examine associations between sociodemographic features and trust and between trust and health behaviors. Results: The combined data included 582 634 responses across 24 survey waves, reflecting 443 455 unique respondents. The unweighted mean (SD) age was 43.3 (16.6) years; 288 186 respondents (65.0%) reported female gender; 21 957 (5.0%) identified as Asian American, 49 428 (11.1%) as Black, 38 423 (8.7%) as Hispanic, 3138 (0.7%) as Native American, 5598 (1.3%) as Pacific Islander, 315 278 (71.1%) as White, and 9633 (2.2%) as other race and ethnicity (those who selected "Other" from a checklist). Overall, the proportion of adults reporting a lot of trust for physicians and hospitals decreased from 71.5% (95% CI, 70.7%-72.2%) in April 2020 to 40.1% (95% CI, 39.4%-40.7%) in January 2024. In regression models, features associated with lower trust as of spring and summer 2023 included being 25 to 64 years of age, female gender, lower educational level, lower income, Black race, and living in a rural setting. These associations persisted even after controlling for partisanship. In turn, greater trust was associated with greater likelihood of vaccination for SARS-CoV-2 (adjusted odds ratio [OR], 4.94; 95 CI, 4.21-5.80) or influenza (adjusted OR, 5.09; 95 CI, 3.93-6.59) and receiving a SARS-CoV-2 booster (adjusted OR, 3.62; 95 CI, 2.99-4.38). Conclusions and Relevance: This survey study of US adults suggests that trust in physicians and hospitals decreased during the COVID-19 pandemic. As lower levels of trust were associated with lesser likelihood of pursuing vaccination, restoring trust may represent a public health imperative.

Tracking COVID-19 Infections Using Survey Data on Rapid At-Home Tests.

Importance: Identifying and tracking new infections during an emerging pandemic is crucial to design and deploy interventions to protect populations and mitigate the pandemic's effects, yet it remains a challenging task. Objective: To characterize the ability of nonprobability online surveys to longitudinally estimate the number of COVID-19 infections in the population both in the presence and absence of institutionalized testing. Design, Setting, and Participants: Internet-based online nonprobability surveys were conducted among residents aged 18 years or older across 50 US states and the District of Columbia, using the PureSpectrum survey vendor, approximately every 6 weeks between June 1, 2020, and January 31, 2023, for a multiuniversity consortium-the COVID States Project. Surveys collected information on COVID-19 infections with representative state-level quotas applied to balance age, sex, race and ethnicity, and geographic distribution. Main Outcomes and Measures: The main outcomes were (1) survey-weighted estimates of new monthly confirmed COVID-19 cases in the US from January 2020 to January 2023 and (2) estimates of uncounted test-confirmed cases from February 1, 2022, to January 1, 2023. These estimates were compared with institutionally reported COVID-19 infections collected by Johns Hopkins University and wastewater viral concentrations for SARS-CoV-2 from Biobot Analytics. Results: The survey spanned 17 waves deployed from June 1, 2020, to January 31, 2023, with a total of 408 515 responses from 306 799 respondents (mean [SD] age, 42.8 [13.0] years; 202 416 women [66.0%]). Overall, 64 946 respondents (15.9%) self-reported a test-confirmed COVID-19 infection. National survey-weighted test-confirmed COVID-19 estimates were strongly correlated with institutionally reported COVID-19 infections (Pearson correlation, r = 0.96; P < .001) from April 2020 to January 2022 (50-state correlation mean [SD] value, r = 0.88 [0.07]). This was before the government-led mass distribution of at-home rapid tests. After January 2022, correlation was diminished and no longer statistically significant (r = 0.55; P = .08; 50-state correlation mean [SD] value, r = 0.48 [0.23]). In contrast, survey COVID-19 estimates correlated highly with SARS-CoV-2 viral concentrations in wastewater both before (r = 0.92; P < .001) and after (r = 0.89; P < .001) January 2022. Institutionally reported COVID-19 cases correlated (r = 0.79; P < .001) with wastewater viral concentrations before January 2022, but poorly (r = 0.31; P = .35) after, suggesting that both survey and wastewater estimates may have better captured test-confirmed COVID-19 infections after January 2022. Consistent correlation patterns were observed at the state level. Based on national-level survey estimates, approximately 54 million COVID-19 cases were likely unaccounted for in official records between January 2022 and January 2023. Conclusions and Relevance: This study suggests that nonprobability survey data can be used to estimate the temporal evolution of test-confirmed infections during an emerging disease outbreak. Self-reporting tools may enable government and health care officials to implement accessible and affordable at-home testing for efficient infection monitoring in the future.

Cognitive Symptoms of Post-COVID-19 Condition and Daily Functioning.

Importance: The frequent occurrence of cognitive symptoms in post-COVID-19 condition has been described, but the nature of these symptoms and their demographic and functional factors are not well characterized in generalizable populations. Objective: To investigate the prevalence of self-reported cognitive symptoms in post-COVID-19 condition, in comparison with individuals with prior acute SARS-CoV-2 infection who did not develop post-COVID-19 condition, and their association with other individual features, including depressive symptoms and functional status. Design, Setting, and Participants: Two waves of a 50-state nonprobability population-based internet survey conducted between December 22, 2022, and May 5, 2023. Participants included survey respondents aged 18 years and older. Exposure: Post-COVID-19 condition, defined as self-report of symptoms attributed to COVID-19 beyond 2 months after the initial month of illness. Main Outcomes and Measures: Seven items from the Neuro-QoL cognition battery assessing the frequency of cognitive symptoms in the past week and patient Health Questionnaire-9. Results: The 14 767 individuals reporting test-confirmed COVID-19 illness at least 2 months before the survey had a mean (SD) age of 44.6 (16.3) years; 568 (3.8%) were Asian, 1484 (10.0%) were Black, 1408 (9.5%) were Hispanic, and 10 811 (73.2%) were White. A total of 10 037 respondents (68.0%) were women and 4730 (32.0%) were men. Of the 1683 individuals reporting post-COVID-19 condition, 955 (56.7%) reported at least 1 cognitive symptom experienced daily, compared with 3552 of 13 084 (27.1%) of those who did not report post-COVID-19 condition. More daily cognitive symptoms were associated with a greater likelihood of reporting at least moderate interference with functioning (unadjusted odds ratio [OR], 1.31 [95% CI, 1.25-1.36]; adjusted [AOR], 1.30 [95% CI, 1.25-1.36]), lesser likelihood of full-time employment (unadjusted OR, 0.95 [95% CI, 0.91-0.99]; AOR, 0.92 [95% CI, 0.88-0.96]) and greater severity of depressive symptoms (unadjusted coefficient, 1.40 [95% CI, 1.29-1.51]; adjusted coefficient 1.27 [95% CI, 1.17-1.38). After including depressive symptoms in regression models, associations were also found between cognitive symptoms and at least moderate interference with everyday functioning (AOR, 1.27 [95% CI, 1.21-1.33]) and between cognitive symptoms and lower odds of full-time employment (AOR, 0.92 [95% CI, 0.88-0.97]). Conclusions and Relevance: The findings of this survey study of US adults suggest that cognitive symptoms are common among individuals with post-COVID-19 condition and associated with greater self-reported functional impairment, lesser likelihood of full-time employment, and greater depressive symptom severity. Screening for and addressing cognitive symptoms is an important component of the public health response to post-COVID-19 condition.

Conspiratorial thinking in a 50-state survey of American adults.

Background: While the NIMH Research Domain Criteria framework stresses understanding how neuropsychiatric phenotypes vary across populations, little is known outside of small clinical cohorts about conspiratorial thoughts as an aspect of cognition. Methods: We conducted a 50-state non-probability internet survey conducted in 6 waves between October 6, 2022 and January 29, 2024, with respondents age 18 and older. Respondents completed the American Conspiratorial Thinking Scale (ACTS) and the 9-item Patient Health Questionnaire (PHQ-9). Survey-weighted regression models were used to examine sociodemographic and clinical associations with ACTS score, and associations with vaccination status. Results: Across the 6 survey waves, there were 123,781 unique individuals. After reweighting, a total of 78.6% of respondents somewhat or strongly agreed with at least one conspiratorial idea; 19.0% agreed with all four of them. More conspiratorial thoughts were reported among those age 25 - 54, males, individuals who finished high school but did not start or complete college, those with household income between $25,000 and $50,000 per year, and those who reside in rural areas, as well as those with greater levels of depressive symptoms. Endorsing more conspiratorial thoughts was associated with a significantly lower likelihood of being vaccinated against COVID-19. Discussion: A substantial proportion of US adults endorsed at least some conspiratorial thinking, which varied widely across population subgroups. The extent of correlation with non-vaccination suggests the importance of considering such thinking in designing public health strategies.

Prevalence and correlates of irritability among U.S. adults.

This study aimed to characterize the prevalence of irritability among U.S. adults, and the extent to which it co-occurs with major depressive and anxious symptoms. A non-probability internet survey of individuals 18 and older in 50 U.S. states and the District of Columbia was conducted between November 2, 2023, and January 8, 2024. Regression models with survey weighting were used to examine associations between the Brief Irritability Test (BITe5) and sociodemographic and clinical features. The survey cohort included 42,739 individuals, mean age 46.0 (SD 17.0) years; 25,001 (58.5%) identified as women, 17,281 (40.4%) as men, and 457 (1.1%) as nonbinary. A total of 1218(2.8%) identified as Asian American, 5971 (14.0%) as Black, 5348 (12.5%) as Hispanic, 1775 (4.2%) as another race, and 28,427 (66.5%) as white. Mean irritability score was 13.6 (SD 5.6) on a scale from 5 to 30. In linear regression models, irritability was greater among respondents who were female, younger, had lower levels of education, and lower household income. Greater irritability was associated with likelihood of thoughts of suicide in logistic regression models adjusted for sociodemographic features (OR 1.23, 95% CI 1.22-1.24). Among 1979 individuals without thoughts of suicide on the initial survey assessed for such thoughts on a subsequent survey, greater irritability was also associated with greater likelihood of thoughts of suicide being present (adjusted OR 1.17, 95% CI 1.12-1.23). The prevalence of irritability and its association with thoughts of suicide suggests the need to better understand its implications among adults outside of acute mood episodes.

Media use and vaccine resistance.

Public health requires collective action-the public best addresses health crises when individuals engage in prosocial behaviors. Failure to do so can have dire societal and economic consequences. This was made clear by the disjointed, politicized response to COVID-19 in the United States. Perhaps no aspect of the pandemic exemplified this challenge more than the sizeable percentage of individuals who delayed or refused vaccination. While scholars, practitioners, and the government devised a range of communication strategies to persuade people to get vaccinated, much less attention has been paid to where the unvaccinated could be reached. We address this question using multiple waves of a large national survey as well as various secondary data sets. We find that the vaccine resistant seems to predictably obtain information from conservative media outlets (e.g. Fox News) while the vaccinated congregate around more liberal outlets (e.g. MSNBC). We also find consistent evidence that vaccine-resistant individuals often obtain COVID-19 information from various social media, most notably Facebook, rather than traditional media sources. Importantly, such individuals tend to exhibit low institutional trust. While our results do not suggest a failure of sites such as Facebook's institutional COVID-19 efforts, as the counterfactual of no efforts is unknown, they do highlight an opportunity to reach those who are less likely to take vital actions in the service of public health.

Community Mobility and Depressive Symptoms During the COVID-19 Pandemic in the United States.

Importance: Marked elevation in levels of depressive symptoms compared with historical norms have been described during the COVID-19 pandemic, and understanding the extent to which these are associated with diminished in-person social interaction could inform public health planning for future pandemics or other disasters. Objective: To describe the association between living in a US county with diminished mobility during the COVID-19 pandemic and self-reported depressive symptoms, while accounting for potential local and state-level confounding factors. Design, Setting, and Participants: This survey study used 18 waves of a nonprobability internet survey conducted in the United States between May 2020 and April 2022. Participants included respondents who were 18 years and older and lived in 1 of the 50 US states or Washington DC. Main Outcome and Measure: Depressive symptoms measured by the Patient Health Questionnaire-9 (PHQ-9); county-level community mobility estimates from mobile apps; COVID-19 policies at the US state level from the Oxford stringency index. Results: The 192 271 survey respondents had a mean (SD) of age 43.1 (16.5) years, and 768 (0.4%) were American Indian or Alaska Native individuals, 11 448 (6.0%) were Asian individuals, 20 277 (10.5%) were Black individuals, 15 036 (7.8%) were Hispanic individuals, 1975 (1.0%) were Pacific Islander individuals, 138 702 (72.1%) were White individuals, and 4065 (2.1%) were individuals of another race. Additionally, 126 381 respondents (65.7%) identified as female and 65 890 (34.3%) as male. Mean (SD) depression severity by PHQ-9 was 7.2 (6.8). In a mixed-effects linear regression model, the mean county-level proportion of individuals not leaving home was associated with a greater level of depression symptoms (ß, 2.58; 95% CI, 1.57-3.58) after adjustment for individual sociodemographic features. Results were similar after the inclusion in regression models of local COVID-19 activity, weather, and county-level economic features, and persisted after widespread availability of COVID-19 vaccination. They were attenuated by the inclusion of state-level pandemic restrictions. Two restrictions, mandatory mask-wearing in public (ß, 0.23; 95% CI, 0.15-0.30) and policies cancelling public events (ß, 0.37; 95% CI, 0.22-0.51), demonstrated modest independent associations with depressive symptom severity. Conclusions and Relevance: In this study, depressive symptoms were greater in locales and times with diminished community mobility. Strategies to understand the potential public health consequences of pandemic responses are needed.

A 50-state survey study of thoughts of suicide and social isolation among older adults in the United States.

BACKGROUND: We aimed to characterize the prevalence of social disconnection and thoughts of suicide among older adults in the United States, and examine the association between them in a large naturalistic study. METHODS: We analyzed data from 6 waves of a fifty-state non-probability survey among US adults conducted between February and December 2021. The internet-based survey collected the PHQ-9, as well as multiple measures of social connectedness. We applied multiple logistic regression to analyze the association between presence of thoughts of suicide and social disconnection. Exploratory analysis, using generalized random forests, examined heterogeneity of effects across sociodemographic groups. RESULTS: Of 16,164 survey respondents age 65 and older, mean age was 70.9 (SD 5.0); the cohort was 61.4 % female and 29.6 % male; 2.0 % Asian, 6.7 % Black, 2.2 % Hispanic, and 86.8 % White. A total of 1144 (7.1 %) reported thoughts of suicide at least several days in the prior 2 week period. In models adjusted for sociodemographic features, households with 3 or more additional members (adjusted OR 1.73, 95 % CI 1.28-2.33) and lack of social supports, particularly emotional supports (adjusted OR 2.60, 95 % CI 2.09-3.23), were independently associated with greater likelihood of reporting such thoughts, as was greater reported loneliness (adjusted OR 1.75, 95 % CI 1.64-1.87). The effects of emotional support varied significantly across sociodemographic groups. CONCLUSIONS: Thoughts of suicide are common among older adults in the US, and associated with lack of social support, but not with living alone. TRIAL REGISTRATION: NA.

Association of Major Depressive Symptoms With Endorsement of COVID-19 Vaccine Misinformation Among US Adults.

Importance: Misinformation about COVID-19 vaccination may contribute substantially to vaccine hesitancy and resistance. Objective: To determine if depressive symptoms are associated with greater likelihood of believing vaccine-related misinformation. Design, Setting, and Participants: This survey study analyzed responses from 2 waves of a 50-state nonprobability internet survey conducted between May and July 2021, in which depressive symptoms were measured using the Patient Health Questionnaire 9-item (PHQ-9). Survey respondents were aged 18 and older. Population-reweighted multiple logistic regression was used to examine the association between moderate or greater depressive symptoms and endorsement of at least 1 item of vaccine misinformation, adjusted for sociodemographic features. The association between depressive symptoms in May and June, and new support for misinformation in the following wave was also examined. Exposures: Depressive symptoms. Main Outcomes and Measures: The main outcome was endorsing any of 4 common vaccine-related statements of misinformation. Results: Among 15 464 survey respondents (9834 [63.6%] women and 5630 [36.4%] men; 722 Asian respondents [4.7%], 1494 Black respondents [9.7%], 1015 Hispanic respondents [6.6%], and 11 863 White respondents [76.7%]; mean [SD] age, 47.9 [17.5] years), 4164 respondents (26.9%) identified moderate or greater depressive symptoms on the PHQ-9, and 2964 respondents (19.2%) endorsed at least 1 vaccine-related statement of misinformation. Presence of depression was associated with increased likelihood of endorsing misinformation (crude odds ratio [OR], 2.33; 95% CI, 2.09-2.61; adjusted OR, 2.15; 95% CI, 1.91-2.43). Respondents endorsing at least 1 misinformation item were significantly less likely to be vaccinated (crude OR, 0.40; 95% CI, 0.36-0.45; adjusted OR, 0.45; 95% CI, 0.40-0.51) and more likely to report vaccine resistance (crude OR, 2.54; 95% CI, 2.21-2.91; adjusted OR, 2.68; 95% CI, 2.89-3.13). Among 2809 respondents who answered a subsequent survey in July, presence of depression in the first survey was associated with greater likelihood of endorsing more misinformation compared with the prior survey (crude OR, 1.98; 95% CI, 1.42-2.75; adjusted OR, 1.63; 95% CI, 1.14-2.33). Conclusions and Relevance: This survey study found that individuals with moderate or greater depressive symptoms were more likely to endorse vaccine-related misinformation, cross-sectionally and at a subsequent survey wave. While this study design cannot address causation, the association between depression and spread and impact of misinformation merits further investigation.