The Association Between Anemia of Chronic Inflammation and Alzheimer's Disease and Related Dementias

Systemic inflammation in Aβ1-40-induced Alzheimer's disease model: New translational opportunities

Alzheimer disease (AD) is the most frequent cause of dementia, and the most common neurodegenerative disease, which is characterized by memory impairment, neuronal death, and synaptic loss in the hippocampus. Sporadic late-onset AD, which accounts for over 95 % of disease cases, is a multifactorial pathology with complex etiology and pathogenesis. Nowadays, neuroinflammation is considered the third most important component of AD pathogenesis in addition to amyloid peptide generation and deposition. Neuroinflammation is associated with the impairment of blood-brain barrier and leakage of inflammatory mediators into the periphery with developing systemic inflammatory responses. Systemic inflammation is currently considered one of the therapeutic targets for AD treatment, that necessitates in-depth study of this phenomenon in appropriate non-transgenic animal models. This study was aimed to explore systemic inflammatory manifestations in rats with Aβ1-40-induced AD. The impairment of spatial memory and cognitive flexibility in Aβ1-40-lesioned rats was accompanied by pronounced systemic inflammation, which was confirmed by commonly accepted biomarkers: increased hematological indices of systemic inflammation (NLR, dNLR, LMR, PLR and SII), signs of anemia of inflammation or chronic diseases, and pro-inflammatory polarized activation of circulating phagocytes. In addition, markers of systemic inflammation strongly correlated with disorders of remote cognitive flexibility in Aβ1-40-lesioned rats. These results indicate, that Aβ1-40-induced AD model permits the investigation of specific element of the disease - systemic inflammation in addition to well reproduced neuroinflammation and impairment of spatial memory and cognitive flexibility. It increases translational value of this well-known model.

Subjective cognitive concerns, APOE ε4, PTSD symptoms, and risk for dementia among older veterans

BACKGROUND

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups.

METHODS

Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older.

RESULTS

PTSD symptoms (B = 0.50-0.52, p < 1E-250) and probable TBI (B = 0.05-0.19, p = 1.51E-07 - 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13-1.21), APOE ε4 (HR = 1.73-2.05) and SCC (HR = 1.18-1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18).

CONCLUSIONS

The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors.

Role of Anemia in Dementia Risk Among Veterans With Incident CKD

RATIONALE & OBJECTIVE

Although some evidence exists of increased dementia risk from anemia, it is unclear whether this association persists among adults with CKD. Anemia may be a key marker for dementia among adults with CKD, so we evaluated whether anemia is associated with an increased risk of dementia among adults with CKD.

STUDY DESIGN

Retrospective cohort study.

SETTING & PARTICIPANTS

The study included 620,095 veterans aged≥45 years with incident stage 3 CKD (estimated glomerular filtration rate [eGFR]<60mL/min/1.73m2) between January 2005 and December 2016 in the US Veterans Health Administration system and followed through December 31, 2018, for incident dementia, kidney failure, or death.

EXPOSURE

Anemia was assessed based on the average of hemoglobin levels (g/L) during the 2 years before the date of incident CKD and categorized as normal, mild, or moderate/severe anemia (≥12.0, 11.0-11.9,<11.0g/dL, respectively, for women, and≥13.0, 11.0-12.9,<11.0g/dL for men).

OUTCOME

Dementia and the composite outcome of kidney failure or death.

ANALYTICAL APPROACH

Adjusted cause-specific hazard ratios were estimated for each outcome.

RESULTS

At the time of incident CKD, the mean age of the participants was 72 years, 97% were male, and their mean eGFR was 51mL/min per 1.73m2. Over a median 4.1 years of follow-up, 92,306 veterans (15%) developed dementia before kidney failure or death. Compared with the veterans with CKD without anemia, the multivariable-adjusted models showed a 16% (95% CI, 14%-17%) significantly higher risk of dementia for those with mild anemia and a 27% (95% CI, 23%-31%) higher risk with moderate/severe anemia. Combined risk of kidney failure or death was higher at 39% (95% CI, 37%-40%) and 115% (95% CI, 112%-119%) for mild and moderate/severe anemia, respectively, compared with no anemia.

LIMITATIONS

Residual confounding from the observational study design. Findings may not be generalizable to the broader US population.

CONCLUSIONS

Anemia was significantly associated with an increased risk of dementia among veterans with incident CKD, underscoring the role of anemia as a predictor of dementia risk.

PLAIN-LANGUAGE SUMMARY

Adults with chronic kidney disease (CKD) often have anemia. Prior studies among adults in the general population suggest anemia is a risk factor for dementia, though it is unclear whether this association persists among adults with CKD. In this large study of veterans in the United States, we studied the association between anemia and the risk of 2 important outcomes in this population: (1) dementia and (2) kidney failure or death. We found that anemia was associated with a greater risk of dementia as well as risk of kidney failure or death. The study findings therefore emphasize the role of anemia as a key predictor of dementia risk among adults with CKD.

Fatigue in Alzheimer's disease: biological basis and clinical management-a narrative review

BACKGROUND

Fatigue is a common symptom in neurodegenerative diseases and is associated with decreased cognitive performances. A full knowledge of the causes and physiopathological pathways leading to fatigue in Alzheimer's disease could help treating this symptom and obtain positive effects on cognitive functions.

OBJECTIVES

To provide an overview of the clinical conditions and the biological mechanisms leading to fatigue in Alzheimer's disease patients. To review the recent advances on fatigue management and describe the landscape of future possibilities.

METHODS

We performed a narrative review including all type of studies (e.g. cross-sectional and longitudinal analysis, reviews, clinical trials).

RESULTS

We found very few studies considering the symptom fatigue in Alzheimer's disease patients. Populations, designs, and objectives varied across studies rendering comparability across studies difficult to perform. Results from cross-sectional and longitudinal analysis suggest that the amyloid cascade may be involved in the pathogenesis of fatigue and that fatigue may be a prodromal manifestation of Alzheimer's disease. Fatigue and neurodegeneration of Alzheimer's disease could share common brain signatures (i.e. hippocampal atrophy and periventricular leukoaraiosis). Some mechanisms of aging (i.e. inflammation, mitochondrial dysfunction, telomere shortening) may be proposed to play a common underlying role in Alzheimer's disease neurodegeneration and muscle fatigability. Considering treatments, donepezil has been found to reduce cognitive fatigue in a 6-week randomized controlled study. Fatigue is frequently reported as an adverse event in patients treated by anti-amyloid agents in clinical trials.

CONCLUSION

The literature is actually inconclusive about the main causes of fatigue in Alzheimer's disease individuals and its potential treatments. Further research is needed to disentangle the role of several components such as comorbidities, depressive symptoms, iatrogenic factors, physical decline and neurodegeneration itself. Given the clinical relevance of this symptom, it seems to be important to systematically assess fatigue by validated tools in Alzheimer's disease clinical trials.

Assessment of factors influencing physicians' intention to prescribe transfusion using the theory of planned behavior

BACKGROUND

Blood shortage is a persistent problem affecting Taiwan's health-care system. The theory of planned behavior (TPB) has been commonly used in studies of health advocacy. The purpose of this study was to develop a questionnaire measuring clinicians' intention to prescribe transfusion based on the TPB.

METHOD

A questionnaire comprising 15 items for assessing clinicians' intention to prescribe blood transfusion was developed, and it collected demographic characteristics, tested patient blood management (PBM) and perceived knowledge of PBM. Furthermore, the questionnaire contained four subscales related to the TPB. A total of 129 clinicians participated in this pilot study between July and December2020. Item analysis and exploratory factor analysis were conducted to examine the validity and reliability of this measurement instrument.

RESULTS

The results indicated no statistically significant correlations between the demographic characteristics and PBM test scores. Regarding perceived knowledge, the results of a one-way analysis of variance revealed that the effect of age, hierarchy of doctors, and education level were significant. In terms of subjective norms, a significant effect on education level was noted [t (129) = 2.28, p < 0.05], with graduate school graduates receiving higher scores than college graduates. An analysis of variance demonstrated the effects of hierarchy, education level, and medical specialty on perceived behavioral control. The results of the regression analyses revealed that perceived knowledge (β = 0.32, p < 0.01) and subjective norms (β = 0.22, p < 0.05) were significantly related to clinicians' behavioral intentions.

CONCLUSIONS

This study revealed that factors affecting clinicians' blood transfusion management can be explained using the TPB-based questionnaire. This study demonstrated that physicians' perceptions of whether most people approve of PBM and their self-assessment of their PBM knowledge affect their intentions to proceed with PBM. According to this finding, a support system among physicians must be established and maintained to increase physicians' confidence in promoting PBM.

Predictors of cognitive impairment in patients undergoing ileostomy for colorectal cancer: a retrospective analysis

Background

Early detection of cognitive impairment in patients undergoing ileostomy for colorectal cancer may help improve patient outcomes and quality of life. Identifying risk factors and clinically accessible factors is crucial for prevention and treatment.

Objective

This retrospective study aimed to identify risk factors for post-operative cognitive impairment in patients undergoing ileostomy for colorectal cancer and to explore potential factors for its prevention and treatment.

Methods

A total of 108 cases were selected and included in the study. Patient data including general characteristics, disease stage, complications, and chemotherapy status were collected, and sleep quality and cognitive function were assessed using questionnaires and follow-up. Patients were randomly divided into training and validation groups. A random forest model was used to rank clinical features based on their contribution to predicting the prognosis of cancer-related cognitive impairment (CRCI). Nomograms were constructed using the support vector machine-recursive feature elimination (SVM-RFE) method, and the minimal root-mean-square error (RMSE) values were compared to select the best model. Regression analysis was performed to determine independent predictors.

Results

Significant differences were observed in age, body mass index (BMI), alcohol consumption, frequency of physical activity, comorbidity, and cancer-related anemia (CRA) between the CRCI and non-CRCI groups. Random forest analysis revealed that age, BMI, exercise intensity, PSQI scores, and history of hypertension were the most significant predictors of outcome. Univariate logistic regression analysis of 18 variables revealed that age, alcohol consumption, exercise intensity, BMI, and comorbidity were significantly associated with the outcome of CRCI (p < 0.05). Univariate and multivariate models with P-values less than 0.1 and 0.2, respectively, showed better predictive performance for CRCI. The results of univariate analysis were plotted on a nomogram to evaluate the risk of developing CRCI after colorectal cancer surgery. The nomogram was found to have good predictive performance. Finally, regression analysis revealed that age, exercise intensity, BMI, comorbidity, and CRA were independent predictors of CRCI.

Conclusions

This retrospective cohort study revealed that age, exercise intensity, BMI, comorbidity, CRA, and mobility are independent predictors of cognitive impairment in patients undergoing ileostomy for colorectal cancer. Identifying these factors and potential factors may have clinical implications in predicting and managing post-operative cognitive impairment in this patient population.

Alzheimer's disease and related dementias among aging veterans: Examining gene-by-environment interactions with post-traumatic stress disorder and traumatic brain injury

INTRODUCTION

Post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI) confer risk for Alzheimer's disease and related dementias (ADRD).

METHODS

This study from the Million Veteran Program (MVP) evaluated the impact of apolipoprotein E (APOE) ε4, PTSD, and TBI on ADRD prevalence in veteran cohorts of European ancestry (EA; n = 11,112 ADRD cases, 170,361 controls) and African ancestry (AA; n = 1443 ADRD cases, 16,191 controls). Additive-scale interactions were estimated using the relative excess risk due to interaction (RERI) statistic.

RESULTS

PTSD, TBI, and APOE ε4 showed strong main-effect associations with ADRD. RERI analysis revealed significant additive APOE ε4 interactions with PTSD and TBI in the EA cohort and TBI in the AA cohort. These additive interactions indicate that ADRD prevalence associated with PTSD and TBI increased with the number of inherited APOE ε4 alleles.

DISCUSSION

PTSD and TBI history will be an important part of interpreting the results of ADRD genetic testing and doing accurate ADRD risk assessment.

A predictive model for the risk of cognitive impairment in community middle-aged and older adults

Identifying individuals at high risk of cognitive impairment is essential for treatment and prevention strategies. We aimed to develop and validate a prediction model for evaluating the risk of cognitive impairment. Data were from the China Family Panel Studies (CFPS) and China Health and Retirement Longitudinal Study (CHARLS). A total of 14,265 subjects were selected for model development. The area under the curve(AUC) for the training, internal, and external validation sets were 0.775, 0.920, and 0.727, respectively. This model could be used to identify middle-aged and older adults aged 45 years and older at high risk of cognitive impairment.

Comorbidities Incorporated to Improve Prediction for Prevalent Mild Cognitive Impairment and Alzheimer's Disease in the HABS-HD Study

BACKGROUND

Blood biomarkers have the potential to transform Alzheimer's disease (AD) diagnosis and monitoring, yet their integration with common medical comorbidities remains insufficiently explored.

OBJECTIVE

This study aims to enhance blood biomarkers' sensitivity, specificity, and predictive performance by incorporating comorbidities. We assess this integration's efficacy in diagnostic classification using machine learning, hypothesizing that it can identify a confident set of predictive features.

METHODS

We analyzed data from 1,705 participants in the Health and Aging Brain Study-Health Disparities, including 116 AD patients, 261 with mild cognitive impairment, and 1,328 cognitively normal controls. Blood samples were assayed using electrochemiluminescence and single molecule array technology, alongside comorbidity data gathered through clinical interviews and medical records. We visually explored blood biomarker and comorbidity characteristics, developed a Feature Importance and SVM-based Leave-One-Out Recursive Feature Elimination (FI-SVM-RFE-LOO) method to optimize feature selection, and compared four models: Biomarker Only, Comorbidity Only, Biomarker and Comorbidity, and Feature-Selected Biomarker and Comorbidity.

RESULTS

The combination model incorporating 17 blood biomarkers and 12 comorbidity variables outperformed single-modal models, with NPV12 at 92.78%, AUC at 67.59%, and Sensitivity at 65.70%. Feature selection led to 22 chosen features, resulting in the highest performance, with NPV12 at 93.76%, AUC at 69.22%, and Sensitivity at 70.69%. Additionally, interpretative machine learning highlighted factors contributing to improved prediction performance.

CONCLUSIONS

In conclusion, combining feature-selected biomarkers and comorbidities enhances prediction performance, while feature selection optimizes their integration. These findings hold promise for understanding AD pathophysiology and advancing preventive treatments.

The Cause of Alzheimer's Disease: The Theory of Multipathology Convergence to Chronic Neuronal Stress

The field of Alzheimer's disease (AD) research critically lacks an all-inclusive etiology theory that would integrate existing hypotheses and explain the heterogeneity of disease trajectory and pathologies observed in each individual patient. Here, we propose a novel comprehensive theory that we named: the multipathology convergence to chronic neuronal stress. Our new theory reconsiders long-standing dogmas advanced by previous incomplete theories. Firstly, while it is undeniable that amyloid beta (Aβ) is involved in AD, in the seminal stage of the disease Aβ is unlikely pathogenic. Instead, we hypothesize that the root cause of AD is neuronal stress in the central nervous system (CNS), and Aβ is expressed as part of the physiological response to protect CNS neurons from stress. If there is no return to homeostasis, then Aβ becomes overexpressed, and this includes the generation of longer forms that are more toxic and prone to oligomerization. Secondly, AD etiology is plausibly not strictly compartmentalized within the CNS but may also result from the dysfunction of other physiological systems in the entire body. This view implies that AD may not have a single cause, but rather needs to be considered as a spectrum of multiple chronic pathological modalities converging to the persistent stressing of CNS neurons. These chronic pathological modalities, which include cardiovascular disease, metabolic disorders, and CNS structural changes, often start individually, and over time combine with other chronic modalities to incrementally escalate the amount of stress applied to CNS neurons. We present the case for considering Aβ as a marker of neuronal stress in response to hypoxic, toxic, and starvation events, rather than solely a marker of AD. We also detail numerous human chronic conditions that can lead to neuronal stress in the CNS, making the link with co-morbidities encountered in daily clinical AD practice. Finally, we explain how our theory could be leveraged to improve clinical care for AD and related dementia in personalized medicine paradigms in the near future.

The influence of anaemia on pressure ulcer healing in elderly patients

Anaemia is a common and multifactorial blood disorder in elderly individuals. This condition may be a significant barrier to pressure ulcers healing as it is associated with a decreased level of oxygen being supplied to body tissues. Some nutritional deficiencies such as iron, vitamin B12 and folate may also cause anaemia and have a negative impact on pressure ulcer healing. An increased iron demand in hard-to-heal pressure ulcers is a significant factor associated with the risk of anaemia of chronic disease in elderly patients. Anaemia screening and correction may need to be considered as well as iron supplementation if required in pressure ulcer prevention and management.

A Predictive Model for the Risk of Cognitive Impairment in Patients with Gallstones

OBJECTIVES

Gallstones can cause malnutrition in patients and further lead to cognitive impairment. This study is aimed at constructing a validated clinical prediction model for evaluating the risk of developing cognitive impairment from gallstones.

METHODS

The study was a single-centre crosssectional study. Four models or methods (SVM-RFE, random forest model, Lasso model, and logistics analysis) were analyzed and compared regarding their predictive performance. The model with the best classification performance and predictive power was selected. The AUC index, C-index, and calibration curves were applied to the chosen model to further evaluate its classification and prediction performance. Finally, the nomogram was plotted, and the clinical usability, efficacy, and safety of the nomogram were assessed using decision curve analysis (DCA).

RESULTS

This study included a total of 294 patients with gallstones, of which 110 had cognitive impairment. Factors such as gender, age, education, place of birth, history of alcohol consumption, abdominal circumference, sarcopenia, diabetes, anaemia, depression, and Pittsburgh Sleep Quality Index (PSQI) were incorporated into the model for nomogram construction. The calibration curve showed that the nomogram had good classification performance. Furthermore, the C-index of the model was 0.778 (95% CI, 0.674-0.882) in the test group. The DCA curves indicated that the constructed model had strong clinical applicability, efficacy, and safety.

CONCLUSIONS

This study constructed a cognitive impairment risk prediction model for patients with gallstones with good classification and predictive power. The constructed predictive model allows us to screen patients with gallstones and at high risk of cognitive impairment. These efforts might also help to further increase patient compliance, assist healthcare professionals to better manage patients with gallstones, and ultimately improve their overall health status and quality of life. Future clinical studies should further evaluate the accuracy and clinical usability of this model.

A Prediction Model for Cognitive Impairment Risk in Colorectal Cancer after Chemotherapy Treatment

Background

A prediction model can be developed to predict the risk of cancer-related cognitive impairment in colorectal cancer patients after chemotherapy.

Methods

A regression analysis was performed on 386 colorectal cancer patients who had undergone chemotherapy. Three prediction models (random forest, logistic regression, and support vector machine models) were constructed using collected clinical and pathological data of the patients. Calibration and ROC curves and C-indexes were used to evaluate the selected models. A decision curve analysis (DCA) was used to determine the clinical utility of the line graph.

Results

Three prediction models including a random forest, a logistic regression, and a support vector machine were constructed. The logistic regression model had the strongest predictive power with an area under the curve (AUC) of 0.799. Age, BMI, colostomy, complications, CRA, depression, diabetes, QLQ-C30 score, exercise, hypercholesterolemia, diet, marital status, education level, and pathological stage were included in the nomogram. The C-index (0.826) and calibration curve showed that the nomogram had good predictive ability and the DCA curves indicated that the model had strong clinical utility.

Conclusions

A prediction model with good predictive ability and practical clinical value can be developed for predicting the risk of cognitive impairment in colorectal cancer after chemotherapy.