Recent evidence has documented associations between higher levels of inflammation and social approach behaviors toward close others in laboratory-based tasks. Yet it is unknown if this translates to interactions with close others in daily life. Given that momentary experiences of social connection have both relational and health consequences, this is a critical gap in our knowledge. To address the association between inflammation and momentary social connection experiences in close relationships, 55 participants provided blood samples on two consecutive days, which were assayed for circulating levels of the inflammatory marker interleukin-6 (IL-6). After providing the first blood sample, participants received the annual influenza vaccine as a mild inflammatory challenge. Participants also reported on cognitive, affective, and behavioral indicators of social connection with a specific close other multiple times across the two study days. Results indicated that levels of IL-6 were positively associated with temporally-proximal indicators of momentary social connection with a close other. Specifically, higher levels of IL-6 were associated with greater feelings of comfort from the close other, greater desire to be near them, and higher reported relationship quality. Greater IL-6 reactivity to the vaccine was only associated with increased reported relationship quality. These data add to the existing literature suggesting that higher levels of IL-6 may motivate social approach toward a close other, extending evidence to now include momentary social connection experiences in daily life. 
                        more » 
                        « less   
                    This content will become publicly available on January 1, 2026
                            
                            Role of Metalloproteinases in Diabetes-associated Mild Cognitive Impairment
                        
                    
    
            :Diabetes has been linked to an increased risk of mild cognitive impairment (MCI), a conditioncharacterized by a subtle cognitive decline that may precede the development of dementia. Theunderlying mechanisms connecting diabetes and MCI involve complex interactions between metabolicdysregulation, inflammation, and neurodegeneration. A critical mechanism implicated in diabetes andMCI is the activation of inflammatory pathways. Chronic low-grade inflammation, as observed in diabetes,can lead to the production of pro-inflammatory cytokines such as tumor necrosis factor-alpha(TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β), and interferon-gamma (IFNγ), each of whichcan exacerbate neuroinflammation and contribute to cognitive decline. A crucial enzyme involved inregulating inflammation is ADAM17, a disintegrin, and metalloproteinase, which can cleave and releaseTNF-α from its membrane-bound precursor and cause it to become activated. These processes, inturn, activate additional inflammation-related pathways, such as AKT, NF-κB, NLP3, MAPK, andJAK-STAT pathways. Recent research has provided novel insights into the role of ADAM17 in diabetesand neurodegenerative diseases. ADAM17 is upregulated in both diabetes and Alzheimer's disease,suggesting a shared mechanism and implicating inflammation as a possible contributor to muchbroader forms of pathology and pointing to a possible link between inflammation and the emergenceof MCI. This review provides an overview of the different roles of ADAM17 in diabetes-associatedmild cognitive impairment diseases. It identifies mechanistic connections through which ADAM17and associated pathways may influence the emergence of mild cognitive impairment. 
        more » 
        « less   
        
    
                            - Award ID(s):
- 2021198
- PAR ID:
- 10566851
- Publisher / Repository:
- Current Neuropharmacology
- Date Published:
- Journal Name:
- Current Neuropharmacology
- Volume:
- 23
- Issue:
- 1
- ISSN:
- 1570-159X
- Page Range / eLocation ID:
- 58 to 74
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            The inflammation marker Interleukin 6 (IL-6) typically remains below 5 pg/mL in the serum of healthy individuals but can increase tenfold during inflammation in chronic conditions like COVID-19 and rheumatoid arthritis, as well as acute conditions like sepsis. This study is focused on the rapid detection of IL-6 to monitor both chronic and acute diseases. The novel sensor, designed with gold-coated micropyramids on the electrodes, was fabricated using the two-photon polymerization method, enabling low-volume sensing capabilities (2-3 μL). The micropyramids were surface functionalized with interleukin-6 antibodies towards developing an affinity biosensor specific to the physiological relevant range of IL-6 of 5.1 and 18.8 pg/mL in mild inflammation. Sensing was achieved by measuring impedance changes associated with IL-6 binding to the antibodies on the micropyramids interfaced using electrochemical impedance spectroscopy. It was observed that the signals from the lowest detection concentration was enhanced by 3 times at 1500 hz when the 532 nm green laser was incident on the micropyramids. This innovative approach can be expanded to the detection of cytokines not only in serum but also in respiratory samples. As a result, it opens up new avenues for monitoring local inflammation within the lungs and assessing systemic inflammation levels throughout the body.more » « less
- 
            Abstract INTRODUCTIONIdentifying mild cognitive impairment (MCI) patients at risk for dementia could facilitate early interventions. Using electronic health records (EHRs), we developed a model to predict MCI to all‐cause dementia (ACD) conversion at 5 years. METHODSCox proportional hazards model was used to identify predictors of ACD conversion from EHR data in veterans with MCI. Model performance (area under the receiver operating characteristic curve [AUC] and Brier score) was evaluated on a held‐out data subset. RESULTSOf 59,782 MCI patients, 15,420 (25.8%) converted to ACD. The model had good discriminative performance (AUC 0.73 [95% confidence interval (CI) 0.72–0.74]), and calibration (Brier score 0.18 [95% CI 0.17–0.18]). Age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors, while body mass index, alcohol abuse, and sleep apnea were protective factors. DISCUSSIONEHR‐based prediction model had good performance in identifying 5‐year MCI to ACD conversion and has potential to assist triaging of at‐risk patients. HighlightsOf 59,782 veterans with mild cognitive impairment (MCI), 15,420 (25.8%) converted to all‐cause dementia within 5 years.Electronic health record prediction models demonstrated good performance (area under the receiver operating characteristic curve 0.73; Brier 0.18).Age and vascular‐related morbidities were predictors of dementia conversion.Synthetic data was comparable to real data in modeling MCI to dementia conversion. Key PointsAn electronic health record–based model using demographic and co‐morbidity data had good performance in identifying veterans who convert from mild cognitive impairment (MCI) to all‐cause dementia (ACD) within 5 years.Increased age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors for 5‐year conversion from MCI to ACD.High body mass index, alcohol abuse, and sleep apnea were protective factors for 5‐year conversion from MCI to ACD.Models using synthetic data, analogs of real patient data that retain the distribution, density, and covariance between variables of real patient data but are not attributable to any specific patient, performed just as well as models using real patient data. This could have significant implications in facilitating widely distributed computing of health‐care data with minimized patient privacy concern that could accelerate scientific discoveries.more » « less
- 
            INTRODUCTION: It is unclear whether aggregated plasma protein risk scores (PPRS) could be useful to predict the risks of mild cognitive impairment (MCI) and Alzheimer’s disease (AD). METHODS: The Cox proportional hazard model with the LASSO penalty was used to build the PPRS for MCI and AD in 1,515 Framingham Heart Study Generation2 with 1,128 proteins measured in plasma at exam 5 [cognitive normal (CN)=1,258, MCI=129, AD=128]. RESULTS: MCI PPRS had a hazard ratio (HR) of 6.97[5.34,9.12], with a discriminating power (C-index=82.52%). AD PPRS had an HR of 5.74[4.67,7.05] (C-index=88.15%). Both PPRSs were also significantly associated with cognitive changes, brain-atrophy, and plasma AD biomarkers. Proteins in the MCI and AD PPRSs were enriched in several pathways related to leukocyte, chemotaxis, immunity, inflammation, and cellular migration. DISCUSSION: This study suggests that PPRS serve well to predict the risk of developing MCI and AD as well as cognitive changes and AD related pathogenesis in the brain.more » « less
- 
            Abstract INTRODUCTIONAlzheimer's disease (AD) initiates years prior to symptoms, underscoring the importance of early detection. While amyloid accumulation starts early, individuals with substantial amyloid burden may remain cognitively normal, implying that amyloid alone is not sufficient for early risk assessment. METHODSGiven the genetic susceptibility of AD, a multi‐factorial pseudotime approach was proposed to integrate amyloid imaging and genotype data for estimating a risk score. Validation involved association with cognitive decline and survival analysis across risk‐stratified groups, focusing on patients with mild cognitive impairment (MCI). RESULTSOur risk score outperformed amyloid composite standardized uptake value ratio in correlation with cognitive scores. MCI subjects with lower pseudotime risk score showed substantial delayed onset of AD and slower cognitive decline. Moreover, pseudotime risk score demonstrated strong capability in risk stratification within traditionally defined subgroups such as early MCI, apolipoprotein E (APOE) ε4+ MCI,APOEε4– MCI, and amyloid+ MCI. DISCUSSIONOur risk score holds great potential to improve the precision of early risk assessment. HighlightsAccurate early risk assessment is critical for the success of clinical trials.A new risk score was built from integrating amyloid imaging and genetic data.Our risk score demonstrated improved capability in early risk stratification.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
