Apolipoprotein E genotyping and questionnaire-based assessment of lifestyle risk factors in dyslipidemic patients with a family history of Alzheimer's disease: test development for clinical application

Association of Single Nucleotide Polymorphisms of Cytokine Genes with Depression, Schizophrenia and Bipolar Disorder

Immune gene variants are known to be associated with the risk of psychiatric disorders, their clinical manifestations, and their response to therapy. This narrative review summarizes the current literature over the past decade on the association of polymorphic variants of cytokine genes with risk, severity, and response to treatment for severe mental disorders such as bipolar disorder, depression, and schizophrenia. A search of literature in databases was carried out using keywords related to depressive disorder, bipolar disorder, schizophrenia, inflammation, and cytokines. Gene lists were extracted from publications to identify common genes and pathways for these mental disorders. Associations between polymorphic variants of the IL1B, IL6, and TNFA genes were the most replicated and relevant in depression. Polymorphic variants of the IL1B, IL6, IL6R, IL10, IL17A, and TNFA genes have been associated with schizophrenia. Bipolar disorder has mainly been associated with polymorphic variants of the IL1B gene. Interestingly, the IL6R gene polymorphism (rs2228145) was associated with all three diseases. Some cytokine genes have also been associated with clinical presentation and response to pharmacotherapy. There is also evidence that some specific polymorphic variants may affect the expression of cytokine genes. Thus, the data from this review indicate a link between neuroinflammation and severe mental disorders.

Association between dementia parental family history and mid-life modifiable risk factors for dementia: a cross-sectional study using propensity score matching within the Lifelines cohort

OBJECTIVE

Individuals with a parental family history (PFH) of dementia have an increased risk to develop dementia, regardless of genetic risks. The aim of this study is to investigate the association between a PFH of dementia and currently known modifiable risk factors for dementia among middle-aged individuals using propensity score matching (PSM).

DESIGN

A cross-sectional study.

SETTING AND PARTICIPANTS

A subsample of Lifelines (35-65 years), a prospective population-based cohort study in the Netherlands was used.

OUTCOME MEASURES

Fourteen modifiable risk factors for dementia and the overall Lifestyle for Brain Health (LIBRA) score, indicating someone's potential for dementia risk reduction (DRR).

RESULTS

The study population included 89 869 participants of which 10 940 (12.2%) had a PFH of dementia (mean (SD) age=52.95 (7.2)) and 36 389 (40.5%) without a PFH of dementia (mean (SD) age=43.19 (5.5)). Of 42 540 participants (47.3%), PFH of dementia was imputed. After PSM, potential confounding variables were balanced between individuals with and without PFH of dementia. Individuals with a PFH of dementia had more often hypertension (OR=1.19; 95% CI 1.14 to 1.24), high cholesterol (OR=1.24; 95% CI 1.18 to 1.30), diabetes (OR=1.26; 95% CI 1.11 to 1.42), cardiovascular diseases (OR=1.49; 95% CI 1.18 to 1.88), depression (OR=1.23; 95% CI 1.08 to 1.41), obesity (OR=1.14; 95% CI 1.08 to 1.20) and overweight (OR=1.10; 95% CI 1.05 to 1.17), and were more often current smokers (OR=1.20; 95% CI 1.14 to 1.27) and ex-smokers (OR=1.21; 95% CI 1.16 to 1.27). However, they were less often low/moderate alcohol consumers (OR=0.87; 95% CI 0.83 to 0.91), excessive alcohol consumers (OR=0.93; 95% CI 0.89 to 0.98), socially inactive (OR=0.84; 95% CI 0.78 to 0.90) and physically inactive (OR=0.93; 95% CI 0.91 to 0.97). Having a PFH of dementia resulted in a higher LIBRA score (RC=0.15; 95% CI 0.11 to 0.19).

CONCLUSION

We found that having a PFH of dementia was associated with several modifiable risk factors. This suggests that middle-aged individuals with a PFH of dementia are a group at risk and could benefit from DRR. Further research should explore their knowledge, beliefs and attitudes towards DRR, and whether they are willing to assess their risk and change their lifestyle to reduce dementia risk.

Towards AI-Enabled Multimodal Diagnostics and Management of COVID-19 and Comorbidities in Resource-Limited Settings

A conceptual artificial intelligence (AI)-enabled framework is presented in this study involving triangulation of various diagnostic methods for management of coronavirus disease 2019 (COVID-19) and its associated comorbidities in resource-limited settings (RLS). The proposed AI-enabled framework will afford capabilities to harness low-cost polymerase chain reaction (PCR)-based molecular diagnostics, radiological image-based assessments, and end-user provided information for the detection of COVID-19 cases and management of symptomatic patients. It will support self-data capture, clinical risk stratification, explanation-based intelligent recommendations for patient triage, disease diagnosis, patient treatment, contact tracing, and case management. This will enable communication with end-users in local languages through cheap and accessible means, such as WhatsApp/Telegram, social media, and SMS, with careful consideration of the need for personal data protection. The objective of the AI-enabled framework is to leverage multimodal diagnostics of COVID-19 and associated comorbidities in RLS for the diagnosis and management of COVID-19 cases and general support for pandemic recovery. We intend to test the feasibility of implementing the proposed framework through community engagement in sub-Saharan African (SSA) countries where many people are living with pre-existing comorbidities. A multimodal approach to disease diagnostics enabling access to point-of-care testing is required to reduce fragmentation of essential services across the continuum of COVID-19 care.

A cross-sectional study of inpatients with late stage of dementia in Southeast China and the associations between biochemical parameters and apolipoprotein E genotypes

Background

The purpose of this study was to analyze the disease distribution of patients in the late stage of dementia through a cross-sectional investigation and to clarify the association between apolipoprotein E (APOE) genotypes and the serum levels of total cholesterol, total triglycerides, and blood glucose in the late-stage Alzheimer’s disease (AD) patients.

Methods

Patients who were in the late stage of dementia in a mental health center were enrolled in this study. A broad battery of neuropsychological tests and neuroimaging was applied to make the diagnosis. The APOE genotype was determined by the multiplex amplification refractory mutation system polymerase chain reaction. The association between APOE genotype and the blood level of biochemical parameters was studied.

Results

A total of 155 patients were enrolled in this study. The majority of patients had AD (67.8%), followed by vascular dementia (15.5%), mixed dementia (9%), and others (7.7%). The APOE ε4 allele frequency was significantly different in the different groups. The serum level of total cholesterol (TC) in APOE ε4 carriers was higher than in non-carriers (P<0.05). No statistically significant differences were found in the blood glucose and triglycerides (TG) levels between these two groups.

Conclusion

To our knowledge, this is the first paper to study the characteristics of late-stage dementia in hospital patients in Southeast China. We found that the disease distribution was quite consistent with previous prevalence studies. Moreover, we found that the serum level of TC was higher in APOE ε4 carriers group. However, no association was found between the APOE ε4 allele and serum levels of glucose, TC and TG in the late stage of AD.