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Wei Y, Sun D, Jaiswal S, He Y, Liu X, Wang J. Association of lifestyle with valvular heart disease progression and life expectancy among elderly people from different socioeconomic backgrounds. BMC Med 2024; 22:367. [PMID: 39237933 PMCID: PMC11378404 DOI: 10.1186/s12916-024-03576-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 08/22/2024] [Indexed: 09/07/2024] Open
Abstract
BACKGROUND Current cardiovascular prevention strategies are based on studies that seldom include valvular heart disease (VHD). The role of modifiable lifestyle factors on VHD progression and life expectancy among the elderly with different socioeconomic statuses (SES) remains unknown. METHODS This cohort study included 164,775 UK Biobank participants aged 60 years and older. Lifestyle was determined using a five-factor scoring system covering smoking status, obesity, physical activity, diet, and sleep patterns. Based on this score, participants were then classified into "poor," "moderate," or "ideal" lifestyle groups. SES was classified as high or low based on the Townsend Deprivation Index. The association of lifestyle with major VHD progression was evaluated using a multistate mode. The life table method was employed to determine life expectancy with VHD and without VHD. RESULTS The UK Biobank documented 5132 incident VHD cases with a mean follow-up of 12.3 years and 1418 deaths following VHD with a mean follow-up of 6.0 years. Compared to those with a poor lifestyle, women and men followed an ideal lifestyle had lower hazard ratios for incident VHD (0.66 with 95% CI, 0.59-0.73 for women and 0.77 with 95% CI, 0.71-0.83 for men) and for post-VHD mortality (0.58 for women, 95% CI 0.46-0.74 and 0.62 for men, 95% CI 0.54-0.73). When lifestyle and SES were combined, the lower risk of incident VHD and mortality were observed among participants with an ideal lifestyle and high SES compared to participants with an unhealthy lifestyle and low SES. There was no significant interaction between lifestyle and SES in their correlation with the incidence and subsequent mortality of VHD. Among low SES populations, 60-year-old women and men with VHD who followed ideal lifestyles lived 4.2 years (95% CI, 3.8-4.7) and 5.1 years (95% CI, 4.5-5.6) longer, respectively, compared to those with poor lifestyles. In contrast, the life expectancy gain for those without VHD was 4.4 years (95% CI, 4.0-4.8) for women and 5.3 years (95% CI, 4.8-5.7) for men when adhering to an ideal lifestyle versus a poor one. CONCLUSIONS Adopting a healthier lifestyle can significantly slow down the progression from free of VHD to incident VHD and further to death and increase life expectancy for both individuals with and without VHD within diverse socioeconomic elderly populations.
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Affiliation(s)
- Yanxia Wei
- Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, China
- Heart Regeneration and Repair Key Laboratory of Zhejiang province, Hangzhou, 310009, China
| | - Dawei Sun
- Department of Anesthesiology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
| | - Sanjay Jaiswal
- Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, China
- Heart Regeneration and Repair Key Laboratory of Zhejiang province, Hangzhou, 310009, China
| | - Yuxin He
- Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, China
- Heart Regeneration and Repair Key Laboratory of Zhejiang province, Hangzhou, 310009, China
| | - Xianbao Liu
- Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China.
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, China.
- Heart Regeneration and Repair Key Laboratory of Zhejiang province, Hangzhou, 310009, China.
| | - Jian'an Wang
- Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China.
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, China.
- Heart Regeneration and Repair Key Laboratory of Zhejiang province, Hangzhou, 310009, China.
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Li C, Meng X, Zhang J, Wang H, Lu H, Cao M, Sun S, Wang Y. Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study. Cardiovasc Diabetol 2024; 23:231. [PMID: 38965592 PMCID: PMC11225301 DOI: 10.1186/s12933-024-02332-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 06/22/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories. METHODS In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of < 3 abnormal components (waist circumstance, blood pressure, blood glucose, triglycerides, and high-density lipoprotein cholesterol). Normal weight, overweight, and obesity were defined as 18.5 ≤ BMI < 25 kg/m2, 25 ≤ BMI < 30 kg/m2, and BMI ≥ 30 kg/m2, respectively. Genetic predisposition was estimated using the polygenic risk score (PRS). Cox regressions were performed to evaluate the associations of metabolic status, metabolic transitions, and PRS with cardiovascular outcomes and all-cause mortality across BMI categories. RESULTS During a median follow-up of 14.38 years, 31,883 (7.3%) all-cause deaths, 8133 (1.8%) cardiovascular disease (CVD) deaths, and 67,260 (14.8%) CVD cases were documented. Among those with a high PRS, individuals classified as metabolically healthy overweight had the lowest risk of all-cause mortality (hazard ratios [HR] 0.70; 95% confidence interval [CI] 0.65, 0.76) and CVD mortality (HR 0.57; 95% CI 0.50, 0.64) compared to those who were metabolically unhealthy obesity, with the beneficial associations appearing to be greater in the moderate and low PRS groups. Individuals who were metabolically healthy normal weight had the lowest risk of CVD morbidity (HR 0.54; 95% CI 0.51, 0.57). Furthermore, the inverse associations of metabolic status and PRS with cardiovascular outcomes and all-cause mortality across BMI categories were more pronounced among individuals younger than 65 years (Pinteraction < 0.05). Additionally, the combined protective effects of metabolic transitions and PRS on these outcomes among BMI categories were observed. CONCLUSIONS MH status and a low PRS are associated with a lower risk of adverse cardiovascular outcomes and all-cause mortality across all BMI categories. This protective effect is particularly pronounced in individuals younger than 65 years. Further research is required to confirm these findings in diverse populations and to investigate the underlying mechanisms involved.
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Affiliation(s)
- Cancan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Xiaoni Meng
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Jie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Haotian Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Huimin Lu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Meiling Cao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Shengzhi Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China.
| | - Youxin Wang
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China.
- School of Public Health, North China University of Science and Technology, 21 Bohaidadao, Caofeidian, Tangshan, 063210, China.
- Centre for Precision Medicine, Edith Cowan University, Perth, 6027, Australia.
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Tang R, Hu Y, Zhou J, Wang X, Li X, Heianza Y, Qi L. Smoking Timing, Healthy Diet, and Risk of Incident CKD Among Smokers: Findings From UK Biobank. Am J Kidney Dis 2024:S0272-6386(24)00809-6. [PMID: 38909935 DOI: 10.1053/j.ajkd.2024.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/22/2024] [Accepted: 04/08/2024] [Indexed: 06/25/2024]
Abstract
RATIONALE & OBJECTIVE Although smoking is a recognized risk factor for chronic kidney disease (CKD), the relationship between the time smoking is initiated after awakening each day and CKD remains largely unstudied. This study examined the association between this timing and the risk of CKD, and the potential interactions of smoking timing with other risk factors for the occurrence of CKD. STUDY DESIGN Observational cohort study. SETTING & PARTICIPANTS A total of 32,776 participants in the UK Biobank with complete data on the time from waking to the first cigarette and free of prevalent CKD were included. EXPOSURE Time from waking to the first cigarette. OUTCOME Incident CKD cases. ANALYTICAL APPROACH Cox proportional hazards regression was used to investigate the associations between the time smoking is initiated each day and the risk of CKD. The potential interactions of smoking timing with risk factors in relationship to CKD risk were assessed on both multiplicative and additive scales. RESULTS During a median follow-up period of 12 years, 940 incident CKD cases occurred. Shorter durations of time from waking to the first cigarette were associated with a higher risk of incident CKD (P trend=0.01). Compared with>120 minutes, the adjusted hazard ratio (HR) associated with smoking timing was 1.28 (95% CI, 0.92-1.80) for 61-120 minutes, 1.48 (95% CI, 1.11-1.96) for 30-60 minutes, 1.36 (95% CI, 1.01-1.88) for 5-15 minutes, and 1.70 (95% CI, 1.22-2.37) for<5 minutes, respectively. Furthermore, there was a significant additive interaction and multiplicative interactions between the timing of smoking and a healthy diet score (P for additive interaction=0.01; P for multiplicative interaction = 0.004). LIMITATIONS Generalizability, possible residual confounding, limiting causal inference. CONCLUSIONS These findings reveal a significant association between the shorter time from waking to the first cigarette and a higher CKD risk. The magnitude of these associations was greater in the setting of an unhealthy diet. PLAIN-LANGUAGE SUMMARY This study explored the association of the daily timing of first cigarette smoking and the occurrence of kidney disease. Further, we addressed whether this association was influenced by the quality of the diet. The study found that smoking very soon after waking, especially when combined with a poorer quality diet, was associated with a significantly increased risk of developing chronic kidney disease. This research emphasizes the value of healthier lifestyle choices for kidney health.
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Affiliation(s)
- Rui Tang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Ying Hu
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Jian Zhou
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Xuan Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana; Department of Nutrition, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts.
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Meshref M, Ghaith HS, Hammad MA, Shalaby MMM, Ayasra F, Monib FA, Attia MS, Ebada MA, Elsayed H, Shalash A, Bahbah EI. The Role of RIN3 Gene in Alzheimer's Disease Pathogenesis: a Comprehensive Review. Mol Neurobiol 2024; 61:3528-3544. [PMID: 37995081 PMCID: PMC11087354 DOI: 10.1007/s12035-023-03802-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 11/10/2023] [Indexed: 11/24/2023]
Abstract
Alzheimer's disease (AD) is a globally prevalent form of dementia that impacts diverse populations and is characterized by progressive neurodegeneration and impairments in executive memory. Although the exact mechanisms underlying AD pathogenesis remain unclear, it is commonly accepted that the aggregation of misfolded proteins, such as amyloid plaques and neurofibrillary tau tangles, plays a critical role. Additionally, AD is a multifactorial condition influenced by various genetic factors and can manifest as either early-onset AD (EOAD) or late-onset AD (LOAD), each associated with specific gene variants. One gene of particular interest in both EOAD and LOAD is RIN3, a guanine nucleotide exchange factor. This gene plays a multifaceted role in AD pathogenesis. Firstly, upregulation of RIN3 can result in endosomal enlargement and dysfunction, thereby facilitating the accumulation of beta-amyloid (Aβ) peptides in the brain. Secondly, RIN3 has been shown to impact the PICLAM pathway, affecting transcytosis across the blood-brain barrier. Lastly, RIN3 has implications for immune-mediated responses, notably through its influence on the PTK2B gene. This review aims to provide a concise overview of AD and delve into the role of the RIN3 gene in its pathogenesis.
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Affiliation(s)
- Mostafa Meshref
- Department of Neurology, Faculty of Medicine, Al-Azhar University, Cairo, Egypt
| | | | | | | | - Faris Ayasra
- Faculty of Medicine, The Hashemite University, Zarqa, Jordan
| | | | - Mohamed S Attia
- Department of Pharmaceutics, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt
| | | | - Hanaa Elsayed
- Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Ali Shalash
- Department of Neurology, Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - Eshak I Bahbah
- Faculty of Medicine, Al-Azhar University, Damietta, Egypt.
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Aravena JM, Lee J, Schwartz AE, Nyhan K, Wang SY, Levy BR. Beneficial Effect of Societal Factors on APOE-ε2 and ε4 Carriers' Brain Health: A Systematic Review. J Gerontol A Biol Sci Med Sci 2024; 79:glad237. [PMID: 37792627 PMCID: PMC10803122 DOI: 10.1093/gerona/glad237] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Apolipoprotein-E (APOE) ε4 and ε2 are the most prevalent risk-increasing and risk-reducing genetic predictors of Alzheimer's disease, respectively. However, the extent to which societal factors can reduce the harmful impact of APOE-ε4 and enhance the beneficial impact of APOE-ε2 on brain health has not yet been examined systematically. METHODS To fill this gap, we conducted a systematic review searching for studies in MEDLINE, Embase, PsycINFO, and Scopus until June 2023, that included: (a) 1 of 5 social determinants of health (SDH) identified by Healthy People 2030, (b) APOE-ε2 or APOE-ε4 allele carriers, (c) cognitive or brain-biomarker outcomes, and (d) studies with an analysis of how APOE-ε2 and/ or APOE-ε4 carriers differ on outcomes when exposed to SDH. RESULTS From 14 076 articles retrieved, 124 met the inclusion criteria. In most of the studies, exposure to favorable SDH reduced APOE-ε4's detrimental effect and enhanced APOE-ε2's beneficial effect on cognitive and brain-biomarker outcomes (cognition: 70.5%, n: 74/105; brain-biomarkers: 71.4%, n: 20/28). A similar pattern of results emerged in each of the 5 Healthy People 2030 SDH categories, where finishing high school, having resources to satisfy basic needs, less air pollution, less negative external stimuli that can generate stress (eg, negative age stereotypes), and exposure to multiple favorable SDH were associated with better cognitive and brain health among APOE-ε4 and APOE-ε2 carriers. CONCLUSIONS Societal factors can reduce the harmful impact of APOE-ε4 and enhance the beneficial impact of APOE-ε2 on cognitive outcomes. This suggests that plans to reduce dementia should include community-level policies promoting favorable SDH.
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Affiliation(s)
- José M Aravena
- Department of Social & Behavioral Sciences, School of Public Health, Yale University, New Haven, Connecticut, USA
| | - Jakyung Lee
- Institute for Community Care and Health Equity, Chung-Ang University, Seoul, Republic of South Korea
| | - Anna E Schwartz
- Department of Social & Behavioral Sciences, School of Public Health, Yale University, New Haven, Connecticut, USA
| | - Kate Nyhan
- Cushing/Whitney Medical Library, Department of Environmental Health Sciences, School of Public Health, Yale University, New Haven, Connecticut, USA
| | - Shi-Yi Wang
- Department of Chronic Disease Epidemiology, School of Public Health, Yale University, New Haven, Connecticut, USA
| | - Becca R Levy
- Department of Social & Behavioral Sciences, School of Public Health, Yale University, New Haven, Connecticut, USA
- Department of Psychology, Yale University, New Haven, Connecticut, USA
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Petrella JR, Jiang J, Sreeram K, Dalziel S, Doraiswamy PM, Hao W. Personalized Computational Causal Modeling of the Alzheimer Disease Biomarker Cascade. J Prev Alzheimers Dis 2024; 11:435-444. [PMID: 38374750 PMCID: PMC11082854 DOI: 10.14283/jpad.2023.134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
BACKGROUND Mathematical models of complex diseases, such as Alzheimer's disease, have the potential to play a significant role in personalized medicine. Specifically, models can be personalized by fitting parameters with individual data for the purpose of discovering primary underlying disease drivers, predicting natural history, and assessing the effects of theoretical interventions. Previous work in causal/mechanistic modeling of Alzheimer's Disease progression has modeled the disease at the cellular level and on a short time scale, such as minutes to hours. No previous studies have addressed mechanistic modeling on a personalized level using clinically validated biomarkers in individual subjects. OBJECTIVES This study aimed to investigate the feasibility of personalizing a causal model of Alzheimer's Disease progression using longitudinal biomarker data. DESIGN/SETTING/PARTICIPANTS/MEASUREMENTS We chose the Alzheimer Disease Biomarker Cascade model, a widely-referenced hypothetical model of Alzheimer's Disease based on the amyloid cascade hypothesis, which we had previously implemented mathematically as a mechanistic model. We used available longitudinal demographic and serial biomarker data in over 800 subjects across the cognitive spectrum from the Alzheimer's Disease Neuroimaging Initiative. The data included participants that were cognitively normal, had mild cognitive impairment, or were diagnosed with dementia (probable Alzheimer's Disease). The model consisted of a sparse system of differential equations involving four measurable biomarkers based on cerebrospinal fluid proteins, imaging, and cognitive testing data. RESULTS Personalization of the Alzheimer Disease Biomarker Cascade model with individual serial biomarker data yielded fourteen personalized parameters in each subject reflecting physiologically meaningful characteristics. These included growth rates, latency values, and carrying capacities of the various biomarkers, most of which demonstrated significant differences across clinical diagnostic groups. The model fits to training data across the entire cohort had a root mean squared error (RMSE) of 0.09 (SD 0.081) on a variable scale between zero and one, and were robust, with over 90% of subjects showing an RMSE of < 0.2. Similarly, in a subset of subjects with data on all four biomarkers in at least one test set, performance was high on the test sets, with a mean RMSE of 0.15 (SD 0.117), with 80% of subjects demonstrating an RMSE < 0.2 in the estimation of future biomarker points. Cluster analysis of parameters revealed two distinct endophenotypic groups, with distinct biomarker profiles and disease trajectories. CONCLUSION Results support the feasibility of personalizing mechanistic models based on individual biomarker trajectories and suggest that this approach may be useful for reclassifying subjects on the Alzheimer's clinical spectrum. This computational modeling approach is not limited to the Alzheimer Disease Biomarker Cascade hypothesis, and can be applied to any mechanistic hypothesis of disease progression in the Alzheimer's field that can be monitored with biomarkers. Thus, it offers a computational platform to compare and validate various disease hypotheses, personalize individual biomarker trajectories and predict individual response to theoretical prevention and therapeutic intervention strategies.
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Affiliation(s)
- J R Petrella
- Jeffrey R. Petrella, Department of Radiology, Duke University School of Medicine, DUMC - Box 3808 , 27710-3808, NC, USA
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Wang X, Ma H, Li X, Heianza Y, Fonseca V, Qi L. Joint association of loneliness and traditional risk factor control and incident cardiovascular disease in diabetes patients. Eur Heart J 2023; 44:2583-2591. [PMID: 37385629 PMCID: PMC10361009 DOI: 10.1093/eurheartj/ehad306] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 03/22/2023] [Accepted: 05/08/2023] [Indexed: 07/01/2023] Open
Abstract
AIMS To investigate the prospective associations of the loneliness and social isolation scales with cardiovascular disease (CVD) risk in diabetes patients and compare the relative importance of loneliness and social isolation with traditional risk factors. Also, the interactions of loneliness or isolation with the degree of risk factor control in relation to CVD risk were evaluated. METHODS AND RESULTS A total of 18 509 participants diagnosed with diabetes from the UK Biobank were included. A two-item scale and a three-item scale were used to assess loneliness and isolation levels, respectively. The degree of risk factor control was defined as numbers of glycated hemoglobin (HbA1c), blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), smoking, and kidney condition controlled within the target range. During a mean follow-up of 10.7 years, 3247 total CVD incidents were documented, including 2771 coronary heart disease and 701 strokes. In the fully adjusted model, compared with participants with the lowest loneliness score (zero), hazard ratios (95% confidence interval) for CVD were 1.11 (1.02 and 1.20) and 1.26 (1.11 and 1.42) for participants with a loneliness scale of 1 and 2, respectively (P-trend < 0.001). No significant associations were observed for social isolation. Loneliness ranked higher in relative strength for predicting CVD than the lifestyle risk factors in diabetes patients. A significant additive interaction between loneliness and the degree of risk factor control on the risk of CVD was observed (P for additive interaction = 0.005). CONCLUSION Among diabetes patients, loneliness, but not social isolation scale, is associated with a higher risk of CVD and shows an additive interaction with the degree of risk factor control.
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Affiliation(s)
- Xuan Wang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, New Orleans, LA 70112, USA
| | - Hao Ma
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, New Orleans, LA 70112, USA
| | - Xiang Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, New Orleans, LA 70112, USA
| | - Yoriko Heianza
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, New Orleans, LA 70112, USA
| | - Vivian Fonseca
- Section of Endocrinology and Metabolism, Tulane University School of Medicine, New Orleans, LA, USA
- Southeast Louisiana Veterans Health Care System, New Orleans, LA, USA
| | - Lu Qi
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, New Orleans, LA 70112, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA
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Lefterov I, Fitz NF, Lu Y, Koldamova R. APOEε4 and risk of Alzheimer's disease - time to move forward. Front Neurosci 2023; 17:1195724. [PMID: 37274212 PMCID: PMC10235508 DOI: 10.3389/fnins.2023.1195724] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/02/2023] [Indexed: 06/06/2023] Open
Abstract
The inheritance of Apolipoprotein E4 (APOEε4) brings the highest genetic risk of Alzheimer's disease (AD), arguably the highest genetic risk in human pathology. Since the discovery of the association, APOE protein isoforms have been at the center of tens of thousands of studies and reports. While, without a doubt, our knowledge about the normal physiological function of APOE isoforms in the brain has increased tremendously, the questions of how the inheritance of the APOEε4 allele translates into a risk of AD, and the risk is materialized, remain unanswered. Moreover, the knowledge about the risk associated with APOEε4 has not helped design a meaningful preventative or therapeutic strategy. Animal models with targeted replacement of Apoe have been generated and, thanks to the recent NIH/NIA/Alzheimer's disease Association initiative, are now freely available to AD researchers. While helpful in many aspects, none of the available models recapitulates normal physiological transcriptional regulation of the human APOE gene cluster. Changes in epigenetic regulation of APOE alleles in animal models in response to external insults have rarely been if ever, addressed. However, these animal models provide a useful tool to handle questions and investigate protein-protein interactions with proteins expressed by other recently discovered genes and gene variants considered genetic risk factors of AD, like Triggering Receptor expressed on Myeloid cells 2 (TREM2). In this review, we discuss genetic and epigenetic regulatory mechanisms controlling and influencing APOE expression and focus on interactions of APOE and TREM2 in the context of microglia and astrocytes' role in AD-like pathology in animal models.
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Wang X, Ma H, Li X, Heianza Y, Manson JE, Franco OH, Qi L. Association of Cardiovascular Health With Life Expectancy Free of Cardiovascular Disease, Diabetes, Cancer, and Dementia in UK Adults. JAMA Intern Med 2023; 183:340-349. [PMID: 36848126 PMCID: PMC9972243 DOI: 10.1001/jamainternmed.2023.0015] [Citation(s) in RCA: 54] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/03/2023] [Indexed: 03/01/2023]
Abstract
Importance The average life expectancy has increased substantially in the past few decades in most industrialized countries; however, not all of the increased life expectancy is being spent in optimal health, especially among individuals with low socioeconomic status. Objective To quantify the associations between levels of cardiovascular health (CVH), estimated by the American Heart Association's Life's Essential 8 (LE8) metrics, with life expectancy free of major chronic disease, including cardiovascular disease (CVD), diabetes, cancer, and dementia, in UK adults. Design, Setting, and Participants This cohort study included 135 199 adults in the UK Biobank study who were initially free of major chronic disease and had complete data on LE8 metrics. Data analyses were performed in August 2022. Exposures Cardiovascular health levels, as estimated by LE8 score. The LE8 score, which consists of 8 components: (1) diet, (2) physical activity, (3) tobacco/nicotine exposure, (4) sleep, (5) body mass index, (6) non-high-density lipoprotein cholesterol, (7) blood glucose, and (8) blood pressure. The CVH level was evaluated at baseline and categorized into low (LE8 score <50), moderate (LE8 score ≥50 but <80), and high (LE8 score ≥80) levels. Main Outcomes and Measures The primary outcome was the life expectancy free of 4 major chronic diseases (CVD, diabetes, cancer, and dementia). Results Of the 135 199 adults (44.7% men; mean [SD] age, 55.4 [7.9] years) included in the study, a total of 4712, 48 955, and 6748 men had low, moderate, and high CVH levels, respectively, and the corresponding numbers for women were 3661, 52 192, and 18 931. At age 50 years, the estimated disease-free years were 21.5 (95% CI, 21.0-22.0), 25.5 (95% CI, 25.4-25.6), and 28.4 (95% CI, 27.8-29.0) for men with low, moderate, and high CVH levels, respectively; the corresponding estimated disease-free years at age 50 years for women were 24.2 (95% CI, 23.5-24.8), 30.5 (95% CI, 30.4-30.6), and 33.6 (95% CI, 33.1-34.0). Equivalently, men with moderate or high CVH levels lived on average 4.0 (95% CI, 3.4-4.5) or 6.9 (95% CI, 6.1-7.7) longer years free of chronic disease, respectively, at age 50 years, compared with men with low CVH levels. The corresponding longer years lived free of disease for women were 6.3 (95% CI, 5.6-7.0) or 9.4 (95% CI, 8.5-10.2). For participants with high CVH level, there was not a statistically significant difference in disease-free life expectancy between participants with low and other socioeconomic status. Conclusions and Relevance In this cohort study, a high level of CVH, evaluated using the LE8 metrics, was associated with longer life expectancy free of major chronic diseases and may contribute to narrowing socioeconomic health inequalities in both men and women.
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Affiliation(s)
- Xuan Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Hao Ma
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - JoAnn E. Manson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Oscar H. Franco
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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Liu W, Xing S, Wei F, Yao Y, Zhang H, Li YC, Liu Z. Excessive Dietary Salt Intake Exacerbates Cognitive Impairment Progression and Increases Dementia Risk in Older Adults. J Am Med Dir Assoc 2023; 24:125-129.e4. [PMID: 36351463 DOI: 10.1016/j.jamda.2022.10.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 09/26/2022] [Accepted: 10/02/2022] [Indexed: 11/07/2022]
Abstract
OBJECTIVES To investigate excessive dietary salt intake as an independent risk factor of cognitive impairment and dementia in older adults. DESIGN Prospective, population-based cohort study. SETTINGS AND PARTICIPANTS Two thousand forty-one community residents aged ≥60 years were recruited between April 2007 and August 2009 from the Shandong area of China. MEASUREMENTS Participants were classified into low, mild, moderate, and high salt intake groups according to urinary sodium measurements for 7 consecutive days. Global cognitive function was assessed at baseline and biennially thereafter using the Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Dementia Rating Scale (DRS), and Informant Questionnaire on Cognitive Decline in the Elderly. Demographics and apolipoprotein E (APOE) genotype were also obtained for each participant. Participants were monitored for 11.4 ± 2.0 years. RESULTS During follow-up, MMSE, MoCA, and DRS scores decreased progressively faster with increasing salt intake (Padjustment < 0.05 among all intake groups). In total, 319 participants (13.74 per 1000 person-years) developed cognitive impairment. Compared with the low salt intake group, cognitive impairment risk was increased by 75% in the mild group (Padjustment = 0.027), 180% in the moderate group (Padjustment < 0.001), and 330% in the high group (Padjustment < 0.001) after adjustment for age, education, mean, and variability in visit-to-visit systolic and diastolic blood pressure, and APOE genotype. The hazard ratio for cognitive impairment increased by 1.59 (95% CI 1.40-1.79) with each 1-SD increment in salt intake after confounder adjustment (Padjustment < 0.001). CONCLUSIONS AND IMPLICATIONS Excessive dietary salt impairs cognitive function and increases cognitive impairment risk in older adults independently of known risk factors, including hypertension and APOE genotype.
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Affiliation(s)
- Weike Liu
- Department of Cardiology, Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shasha Xing
- Department of Geriatrics, Third Hospital of Lixia District, Jinan, Shandong, China
| | - Fang Wei
- Department of Cardiology, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Yanli Yao
- Department of Cardiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China; School of Basic Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Hua Zhang
- Department of Cardiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China; School of Basic Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Yue-Chun Li
- Department of Cardiology, Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhendong Liu
- Department of Cardiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China; School of Basic Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China.
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