Differential transcriptome expression in human nucleus accumbens as a function of loneliness

Contributions of loneliness to cognitive impairment and dementia in older adults are independent of other risk factors and Alzheimer's pathology: a narrative review

Loneliness significantly contributes to cognitive impairment and dementia in older adults. Loneliness is a distressing feeling resulting from a perceived lack of social connection (i.e., a discrepancy between desired and actual social relationships), while social isolation is a related term that can be defined by number and type of social relationships. Importantly, loneliness is distinct from social isolation in that it is associated with a distressing self-perception. The primary focus of this narrative review is the impact of chronic loneliness on cognitive impairment and dementia among older adults. Loneliness has a significant association with many factors that are related to worse cognition, and therefore we include discussion on health, mental health, as well as the physiological effects of loneliness, neuropathology, and potential treatments. Loneliness has been shown to be related to development of dementia with a hazard ratio (HR) risk comparable to having a single APOE4 gene. The relationship of dementia to loneliness appears to be at least partially independent of other known dementia risk factors that are possibly associated with loneliness, such as depression, educational status, social isolation, and physical activity. Episodic memory is not consistently impacted by loneliness, which would be more typically impaired if the mild cognitive impairment (MCI) or dementia was due to Alzheimer's disease (AD) pathology. In addition, the several longitudinal studies that included neuropathology showed no evidence for a relationship between loneliness and AD neuropathology. Loneliness may decrease resilience, or produce greater cognitive change associated with the same level of AD neuropathology. Intervention strategies to decrease loneliness in older adults have been developed but need to consider key treatment targets beyond social isolation. Loneliness needs to be assessed in all studies of cognitive decline in elders, since it significantly contributes to the variance of cognitive function. It will be useful to better define the underlying mechanism of loneliness effects on cognition to determine if it is similar to other psychological factors related to excessive stress reactivity, such as neuroticism or even depression, which are also associated with cognitive decline. It is important from a health perspective to develop better strategies to decrease loneliness in older adults.

Psychological and neurobiological mechanisms involved in the relationship between loneliness and cognitive decline in older adults

Loneliness, among older adults, is one of the risk factors for developing dementia. Still, little is known about the neurobiological and psychological conditions that link loneliness to cognitive decline. The current study investigated several research aims: First, it sought to identify neurobiological and psychological pathways that may account for the relationship between loneliness and decline across several cognitive domains. These pathways included depressive symptoms, total gray matter volume, and conditional analyses of pro-inflammatory cytokines and brain-derived neurotrophic factor (BDNF) expression. Second, it examined loneliness as a predictor of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Third, it sought to determine whether the relationship between loneliness and cognitive decline is sex-specific in older adults. Longitudinal data were collected from 2130 Rush Memory and Aging Project participants. Participants underwent annual cognitive and psychological assessments and neuroimaging procedures every year. BDNF gene expression was measured in the dorsolateral prefrontal cortex, cytokines were measured in serum, and the final consensus clinical diagnosis was identified at the time of death. All linear mixed and multinomial logistic regression models controlled for age at baseline, education, sex, and APOE genotype. Participants were largely women (73 %), and Caucasian (93 %). The average education was 14.93 (SD = 3.34). The average age at baseline was 80.05 (SD = 7.57). Results showed that gray matter volume and depressive symptoms partially mediated the relationship between loneliness and cognitive decline. There was a significant interaction between loneliness and BDNF expression in relation to cognitive decline. Higher levels of BDNF expression was associated with slower decline in semantic memory and visuospatial ability. Finally, the current study also established that higher levels of loneliness was positively associated with the incidence of AD and other dementias. The present findings support the growing literature, which tends to show that the consequence of loneliness goes beyond the feeling of being isolated. Loneliness may induce physiological changes in our brains, leading to cognitive decline. Future research can explore a wide range of biological and psychological expressions of loneliness to clarify how loneliness relates to dementia.

How does loneliness "get under the skin" to become biologically embedded?

Loneliness is linked to declining physical health across cardiovascular, inflammatory, metabolic, and cognitive domains. As a result, loneliness is increasingly being recognized as a public health threat, though the mechanisms that have been studied do not yet explain all loneliness-related health risk. Potential mechanisms include loneliness having 1.) direct, causal impacts on health, possibly maintained by epigenetic modification, 2.) indirect effects mediated through health-limiting behaviors, and 3.) artifactual associations perhaps related to genetic overlap and reverse causation. In this scoping review, we examine the evidence surrounding each of these pathways, with a particular emphasis on emerging research on epigenetic effects, in order to evaluate how loneliness becomes biologically embedded. We conclude that there are significant gaps in our knowledge of how psychosocial stress may lead to physiological changes, so more work is needed to understand if, how, and when loneliness has a direct influence on health. Hypothalamic-pituitary adrenocortical axis disruptions that lead to changes in gene expression through methylation and the activity of transcription factor proteins are one promising area of research but are confounded by a number of unmeasured factors. Therefore, wok is needed using causally informative designs, such as twin and family studies and intensively longitudinal diary studies.

Co-Expression Network Analysis Identifies Molecular Determinants of Loneliness Associated with Neuropsychiatric and Neurodegenerative Diseases

Loneliness and social isolation are detrimental to mental health and may lead to cognitive impairment and neurodegeneration. Although several molecular signatures of loneliness have been identified, the molecular mechanisms by which loneliness impacts the brain remain elusive. Here, we performed a bioinformatics approach to untangle the molecular underpinnings associated with loneliness. Co-expression network analysis identified molecular 'switches' responsible for dramatic transcriptional changes in the nucleus accumbens of individuals with known loneliness. Loneliness-related switch genes were enriched in cell cycle, cancer, TGF-β, FOXO, and PI3K-AKT signaling pathways. Analysis stratified by sex identified switch genes in males with chronic loneliness. Male-specific switch genes were enriched in infection, innate immunity, and cancer-related pathways. Correlation analysis revealed that loneliness-related switch genes significantly overlapped with 82% and 68% of human studies on Alzheimer's (AD) and Parkinson's diseases (PD), respectively, in gene expression databases. Loneliness-related switch genes, BCAM, NECTIN2, NPAS3, RBM38, PELI1, DPP10, and ASGR2, have been identified as genetic risk factors for AD. Likewise, switch genes HLA-DRB5, ALDOA, and GPNMB are known genetic loci in PD. Similarly, loneliness-related switch genes overlapped in 70% and 64% of human studies on major depressive disorder and schizophrenia, respectively. Nine switch genes, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL, overlapped with known genetic variants in depression. Seven switch genes, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5 were associated with known risk factors for schizophrenia. Collectively, we identified molecular determinants of loneliness and dysregulated pathways in the brain of non-demented adults. The association of switch genes with known risk factors for neuropsychiatric and neurodegenerative diseases provides a molecular explanation for the observed prevalence of these diseases among lonely individuals.

Associations of Social Isolation and Loneliness With Later Dementia

BACKGROUND AND OBJECTIVES

To investigate the independent associations of social isolation and loneliness with incident dementia and to explore the potential neurobiological mechanisms.

METHODS

We utilized the UK Biobank cohort to establish Cox proportional hazard models with social isolation and loneliness as separate exposures. Demographic (sex, age, and ethnicity), socioeconomic (education level, household income, and Townsend deprivation index), biological (body mass index, APOE genotype, diabetes, cancer, cardiovascular disease, and other), cognitive (speed of processing and visual memory), behavioral (current smoker, alcohol intake, and physical activity), and psychological (social isolation or loneliness, depressive symptoms, and neuroticism) factors measured at baseline were adjusted. Then, voxel-wise brainwide association analyses were used to identify gray matter volumes (GMVs) associated with social isolation and with loneliness. Partial least squares regression was performed to test the spatial correlation of GMV differences and gene expression using the Allen Human Brain Atlas.

RESULTS

We included 462,619 participants (mean age at baseline 57.0 years [SD 8.1]). With a mean follow-up of 11.7 years (SD 1.7), 4,998 developed all-cause dementia. Social isolation was associated with a 1.26-fold increased risk of dementia (95% CI, 1.15-1.37) independently of various risk factors including loneliness and depression (i.e., full adjustment). However, the fully adjusted hazard ratio for dementia related to loneliness was 1.04 (95% CI, 0.94-1.16) and 75% of this relationship was attributable to depressive symptoms. Structural MRI data were obtained from 32,263 participants (mean age 63.5 years [SD 7.5]). Socially isolated individuals had lower GMVs in temporal, frontal, and other (e.g., hippocampal) regions. Mediation analysis showed that the identified GMVs partly mediated the association between social isolation at baseline and cognitive function at follow-up. Social isolation-related lower GMVs were related to underexpression of genes that are downregulated in Alzheimer disease and to genes that are involved in mitochondrial dysfunction and oxidative phosphorylation.

DISCUSSION

Social isolation is a risk factor for dementia that is independent of loneliness and many other covariates. Social isolation-related brain structural differences coupled with different molecular functions also support the associations of social isolation with cognition and dementia. Social isolation may thus be an early indicator of an increased risk of dementia.

Individual Differences in Cerebral Perfusion as a Function of Age and Loneliness

Loneliness is defined as the subjective feeling that one's social needs are not satisfied by both quantity and quality of one's social relationships. Loneliness has been linked to a broad range of adverse physical and mental health consequences. There is an interest in identifying the neural and molecular processes by which loneliness adversely affects health. Prior imaging studies reported divergent networks involved in cognitive, emotional, and social processes associated with loneliness. Although loneliness is common among both younger and older adults, it is experienced differently across the lifespan and has different antecedents and consequences. The current study measured regional cerebral blood flow (CBF) using pulsed arterial spin labeling imaging. Forty-five older (M_age = 63.4) and forty-four younger adults (M_age = 20.9) with comparable degrees of loneliness were included. Whole-brain voxel-wise analysis revealed a main effect of age (in superior temporal and supramarginal gyri), but no main effect of loneliness. Furthermore, the age effect was only observed among people who reported higher level of loneliness. These regions have previously been implicated in social- and attention-related functions. The moderation of loneliness on age and regional CBF suggests that younger and older individuals present differential neural manifestations in response to loneliness, even with comparable levels of loneliness.

Neurobiology of loneliness: a systematic review

Loneliness is associated with increased morbidity and mortality. Deeper understanding of neurobiological mechanisms underlying loneliness is needed to identify potential intervention targets. We did not find any systematic review of neurobiology of loneliness. Using MEDLINE and PsycINFO online databases, we conducted a search for peer-reviewed publications examining loneliness and neurobiology. We identified 41 studies (n = 16,771 participants) that had employed various methods including computer tomography (CT), structural magnetic resonance imaging (MRI), functional MRI (fMRI), electroencephalography (EEG), diffusion tensor imaging (DTI), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and post-mortem brain tissue RNA analysis or pathological analysis. Our synthesis of the published findings shows abnormal structure (gray matter volume or white matter integrity) and/or activity (response to pleasant versus stressful images in social versus nonsocial contexts) in the prefrontal cortex (especially medial and dorsolateral), insula (particularly anterior), amygdala, hippocampus, and posterior superior temporal cortex. The findings related to ventral striatum and cerebellum were mixed. fMRI studies reported links between loneliness and differential activation of attentional networks, visual networks, and default mode network. Loneliness was also related to biological markers associated with Alzheimer's disease (e.g., amyloid and tau burden). Although the published investigations have limitations, this review suggests relationships of loneliness with altered structure and function in specific brain regions and networks. We found a notable overlap in the regions involved in loneliness and compassion, the two personality traits that are inversely correlated in previous studies. We have offered recommendations for future research studies of neurobiology of loneliness.

Loneliness-based impaired reward system pathway: Theoretical and clinical analysis and application

Loneliness is a key determinant in the etiology of mental health disorders such as depression and has profound impacts on health, quality of life, and economic productivity. This narrative review uses extant neurobiology and evolutionary literature to propose a construct through which loneliness may induce depression in adulthood via the reward system (including symptom and treatment aspects). Early childhood (distal) factors were found to be important in influencing adult (proximal) factors, which lead to the formulation of the construct. Due to the heterogenous and comorbid nature of depression, a new subtype known as 'reward depression' was distinguished along with distinct symptoms to aid practitioners when assessing patient treatment options. Furthermore, an evolutionary perspective was applied to the current impaired reward construct to discuss how the ancestral purpose and environment (in terms of reward) clashes with the modern one. Finally, theoretical treatment and prevention ideas were examined and discussed, leading into future work that needs to build upon and confirm the outlined construct.

Diurnal rhythms across the human dorsal and ventral striatum

The human striatum can be subdivided into the caudate, putamen, and nucleus accumbens (NAc). Each of these structures have some overlapping and some distinct functions related to motor control, cognitive processing, motivation, and reward. Previously, we used a "time-of-death" approach to identify diurnal rhythms in RNA transcripts in human cortical regions. Here, we identify molecular rhythms across the three striatal subregions collected from postmortem human brain tissue in subjects without psychiatric or neurological disorders. Core circadian clock genes are rhythmic across all three regions and show strong phase concordance across regions. However, the putamen contains a much larger number of significantly rhythmic transcripts than the other two regions. Moreover, there are many differences in pathways that are rhythmic across regions. Strikingly, the top rhythmic transcripts in NAc (but not the other regions) are predominantly small nucleolar RNAs and long noncoding RNAs, suggesting that a completely different mechanism might be used for the regulation of diurnal rhythms in translation and/or RNA processing in the NAc versus the other regions. Further, although the NAc and putamen are generally in phase with regard to timing of expression rhythms, the NAc and caudate, and caudate and putamen, have several clusters of discordant rhythmic transcripts, suggesting a temporal wave of specific cellular processes across the striatum. Taken together, these studies reveal distinct transcriptome rhythms across the human striatum and are an important step in helping to understand the normal function of diurnal rhythms in these regions and how disruption could lead to pathology.

Mapping gene expression in social anxiety reveals the main brain structures involved in this disorder

Social Anxiety Disorder (SAD) is characterized by emotional and attentional biases as well as distorted negative self-beliefs. According this, we proposed to identify the brain structures and hub genes involved in SAD. An analysis in Pubmed and TRANSFAC was conducted and 72 genes were identified. Using Microarray data, from Allen Human Brain Atlas, it was possible to identify three modules of co-expressed genes from our gene set (R package WGCNA). Higher mean gene expression was found in cortico-medial group, basomedial nucleus, ATZ in amygdala and in head and tail of the caudate nucleus, nucleus accumbens and putamen in striatum. Our enrichment analysis identified the followed hub genes: DRD2, HTR1A, JUN, SP1 and HDAC4. We suggest that SAD is explained by delayed extinction of circuitry for conditioned fear. Caused by reduced activation of the dopaminergic and serotonergic systems,due diminished expectation of reward during social interactions.

Blood biomarkers for memory: toward early detection of risk for Alzheimer disease, pharmacogenomics, and repurposed drugs

Short-term memory dysfunction is a key early feature of Alzheimer's disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).

Towards precision medicine for stress disorders: diagnostic biomarkers and targeted drugs

The biological fingerprint of environmental adversity may be key to understanding health and disease, as it encompasses the damage induced as well as the compensatory reactions of the organism. Metabolic and hormonal changes may be an informative but incomplete window into the underlying biology. We endeavored to identify objective blood gene expression biomarkers for psychological stress, a subjective sensation with biological roots. To quantify the stress perception at a particular moment in time, we used a simple visual analog scale for life stress in psychiatric patients, a high-risk group. Then, using a stepwise discovery, prioritization, validation, and testing in independent cohort design, we were successful in identifying gene expression biomarkers that were predictive of high-stress states and of future psychiatric hospitalizations related to stress, more so when personalized by gender and diagnosis. One of the top biomarkers that survived discovery, prioritization, validation, and testing was FKBP5, a well-known gene involved in stress response, which serves as a de facto reassuring positive control. We also compared our biomarker findings with telomere length (TL), another well-established biological marker of psychological stress and show that newly identified predictive biomarkers such as NUB1, APOL3, MAD1L1, or NKTR are comparable or better state or trait predictors of stress than TL or FKBP5. Over half of the top predictive biomarkers for stress also had prior evidence of involvement in suicide, and the majority of them had evidence in other psychiatric disorders, providing a molecular underpinning for the effects of stress in those disorders. Some of the biomarkers are targets of existing drugs, of potential utility in patient stratification, and pharmacogenomics approaches. Based on our studies and analyses, the biomarkers with the best overall convergent functional evidence (CFE) for involvement in stress were FKBP5, DDX6, B2M, LAIR1, RTN4, and NUB1. Moreover, the biomarker gene expression signatures yielded leads for possible new drug candidates and natural compounds upon bioinformatics drug repurposing analyses, such as calcium folinate and betulin. Our work may lead to improved diagnosis and treatment for stress disorders such as PTSD, that result in decreased quality of life and adverse outcomes, including addictions, violence, and suicide.

Connectome-based individualized prediction of loneliness

Loneliness is an increasingly prevalent condition linking with enhanced morbidity and premature mortality. Despite recent proposal on medicalization of loneliness, so far no effort has been made to establish a model capable of predicting loneliness at the individual level. Here, we applied a machine-learning approach to decode loneliness from whole-brain resting-state functional connectivity (RSFC). The relationship between whole-brain RSFC and loneliness was examined in a linear predictive model. The results revealed that individual loneliness could be predicted by within- and between-network connectivity of prefrontal, limbic and temporal systems, which are involved in cognitive control, emotional processing and social perceptions and communications, respectively. Key nodes that contributed to the prediction model comprised regions previously implicated in loneliness, including the dorsolateral prefrontal cortex, lateral orbital frontal cortex, ventromedial prefrontal cortex, caudate, amygdala and temporal regions. Our findings also demonstrated that both loneliness and associated neural substrates are modulated by levels of neuroticism and extraversion. The current data-driven approach provides the first evidence on the predictive brain features of loneliness based on organizations of intrinsic brain networks. Our work represents initial efforts in the direction of making individualized prediction of loneliness that could be useful for diagnosis, prognosis and treatment.

Genetic Contributions to Loneliness and Their Relevance to the Evolutionary Theory of Loneliness

Loneliness is a negative and distressing emotional state that arises from a discrepancy between one's desired and achieved levels of social connectedness. The evolutionary theory of loneliness (ETL) posits that experiencing loneliness is an inherited adaptation that signals that salutary social relations are endangered or damaged and prompts people to reconnect to significant others. The basic tenets of the ETL has led researchers to examine the genetic underpinnings of loneliness. The current review provides an updated overview of genetic studies on loneliness and discusses the importance of genetic research for the ETL. The most recent studies suggest that the many genes that contribute to a small degree to differences in loneliness partially overlap with genes that contribute to neuroticism, but not with depression. In addition, the genetic studies discussed in this review show that genes are unlikely to have a direct effect on loneliness. Instead, environmental factors determine in a dynamic fashion how genes that contribute to loneliness are expressed. Future research on epigenetic processes, such as DNA methylation, can further elucidate the dynamic interplay between genes and the environment and how this interplay contributes to loneliness.

Stress-Related Biosocial Mechanisms of Discrimination and African American Health Inequities

This review describes stress-related biological mechanisms linking interpersonal racism to life course health trajectories among African Americans. Interpersonal racism, a form of social exclusion enacted via discrimination, remains a salient issue in the lives of African Americans, and it triggers a cascade of biological processes originating as perceived social exclusion and registering as social pain. Exposure to discrimination increases sympathetic nervous system activation and upregulates the HPA axis, increasing physiological wear and tear and elevating the risks of cardiometabolic conditions. Consequently, discrimination is associated with morbidities including low birth weight, hypertension, abdominal obesity, and cardiovascular disease. Biological measures can provide important analytic tools to study the interactions between social experiences such as racial discrimination and health outcomes over the life course. We make future recommendations for the study of discrimination and health outcomes, including the integration of neuroscience, genomics, and new health technologies; interdisciplinary engagement; and the diversification of scholars engaged in biosocial inequities research.

Loneliness 5 years ante-mortem is associated with disease-related differential gene expression in postmortem dorsolateral prefrontal cortex

Subjective social isolation, loneliness, is associated with poor mental and physical health, but the underlying molecular mechanisms are poorly understood. Here we analyzed loneliness data collected on average 5 years ante-mortem and RNA gene expression at death in postmortem dorsolateral prefrontal cortex (DLPFC) from 181 participants in the Rush Memory and Aging Project (MAP), a longitudinal, prospective cohort study of common chronic conditions of aging. Our analytic protocol controlled for biographical variables (age, sex, education), psychological and health variables (depressive symptoms, interval between assessment and autopsy, slope of cognitive decline, AD pathology, presence of infarcts) and RNA integrity. Our results are based on a pre-ranked Gene Set Enrichment Analysis (GSEA) at FDR-corrected q-values <0.05, using these collections from the Molecular Signatures Database (v6.0 MSigDB): (1) Hallmarks, (2) Canonical, (3) Gene Ontology (GO), (4) Chemical and Genetic Perturbations, (5) Immunologic Signatures, (6) Oncogenic Signatures, and (7) Cancer Modules. We now report on 337 up-regulated and 43 down-regulated gene sets, among which the most significant ones were associated with Alzheimer's disease, psychiatric illness, immune dysfunction, and cancer. These gene sets constitute attractive targets for future studies into the molecular mechanisms by which loneliness exacerbates a wide range of neurodegenerative, psychiatric, and somatic illnesses.

Religious Orders Study and Rush Memory and Aging Project

BACKGROUND

The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD).

OBJECTIVES

To summarize progress over the past five years and its implications for understanding neurodegenerative diseases.

METHODS

Participants in both studies are older adults who enroll without dementia and agree to detailed longitudinal clinical evaluations and organ donation. The last review summarized findings through the end of 2011. Here we summarize progress and study findings over the past five years and discuss new directions for how these studies can inform on aging and AD in the future.

RESULTS

We summarize 1) findings on the relation of neurobiology to clinical AD; 2) neurobiologic pathways linking risk factors to clinical AD; 3) non-cognitive AD phenotypes including motor function and decision making; 4) the development of a novel drug discovery platform.

CONCLUSION

Complexity at multiple levels needs to be understood and overcome to develop effective treatments and preventions for cognitive decline and AD dementia.

How Does Psychosocial Behavior Contribute to Cognitive Health in Old Age?

With the aging of the U.S. population, the number of cognitively disabled persons is expected to substantially increase in coming decades, underscoring the urgent need for effective interventions. Here, we review the current evidence linking psychosocial factors to late-life cognitive loss and consider the study design needed to illuminate the biologic bases of the associations. We then examine an ongoing study that includes several of the key design elements, the Rush Memory and Aging Project. In this longitudinal clinical-pathological cohort study, indicators of personality, social connectedness, and psychological well-being were shown to predict late-life cognitive outcomes. Participants who died underwent a uniform neuropathologic examination to quantify common dementia-related pathologies. Some psychosocial indicators were associated with cerebral infarction; some indicators modified the association of neurodegenerative pathologies with cognitive loss; and the association of some indicators with cognitive outcomes appears to be independent of the pathologies traditionally associated with late-life dementia. These findings suggest that psychosocial behavior influences late-life cognitive health through multiple neurobiologic mechanisms. A better understanding of these mechanisms may lead to novel strategies for preserving cognitive health in old age.