Association of late-life body mass index with the risk of Alzheimer disease: a 10-year nationwide population-based cohort study

Cho, Su Hwan; Jang, Minseol; Ju, Hyorim; Kang, Min Ju; Yun, Jae Moon; Yun, Jae Won

doi:10.1038/s41598-022-19696-2

Cited by 5 publications

(3 citation statements)

References 41 publications

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“…For individuals with high late-life BMI, AD's HR came out as 0.902. (95% CI 0.79-1.02), while those with greater midlife to late-life BMI reduction had a 20% higher chance of AD (95% CI 0.99-1.42) (Cho et al 2022). Older individuals had a lower Aβ burden and more enormous hippocampal volume.…”

Section: The Obesity Epidemicmentioning

confidence: 96%

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Review of the determinants contributing to the demographics of Alzheimer’s syndrome: Prevention techniques, risk factors, and insights for public health

Verma,

Patel,

Malathi

et al. 2024

Multidiscip. Rev.

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Alzheimer's disease (AD) is the leading cause of memory loss, accounting for 80% of cases and severely impacting daily life and social interactions. The prevalence of AD is expected to grow over the globe as life expectancy improves and the population ages in developing countries will result in a costly disease burden. A combination of societal circumstances and inherent sensitivity that extends throughout a person’s lifetime can cause AD, a challenging and varied disorder. This study aims to provide a comprehensive analysis of the factors that shape the demographics of AD, with a focus on prevention measures. risk factors and their public health consequences. Interventions aimed at addressing multiple risk indicators in non-demented older adults, including those in their middle age, can be able to prevent or postpone the development of AD since the illness is thought to begin generations before clinical evidence appears. Addressing the intricate connection between social and psychological characteristics and Alzheimer’s demography is critical for devising effective preventative measures, early treatments and individualized care for at-risk communities. AD is known to be associated with genetic variables, particularly the APOE ε4 allele. Identifying the disease’s genetic causes is essential for specific preventive and early intervention methods. A balanced diet, frequent physical exercise, cognitive stimulation and social involvement are the preventative treatments for AD. Early identification and intervention hold promise for reducing disease development and public health measures that promote knowledge as well as healthy lives are essential.

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Section: The Obesity Epidemicmentioning

confidence: 96%

“…This research intended to explore AD demographics, including prevention methods, risk factors and public health insights (Franks et al 2021). Figure 1 shows the overall review of factors affecting AD demographics: preventive strategies, risk assessments and public health perspectives in this study (Cho et al 2022).…”

mentioning

confidence: 99%

Review of the determinants contributing to the demographics of Alzheimer’s syndrome: Prevention techniques, risk factors, and insights for public health

Verma,

Patel,

Malathi

et al. 2024

Multidiscip. Rev.

View full text Add to dashboard Cite

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“…Another study showed similar patterns of brain atrophy and AD pathology in obesity compared to AD patients matched by age and sex [ 6 ]. Interestingly, although obesity in midlife is associated with lower brain volumes and a higher risk of AD, obesity in late life (after age 70 years) is associated with decreased AD risk [ 2 , 7 ] and higher BMI is negatively associated with cortical β-amyloid content in older adults [ 8 - 10 ]. In addition, higher body fat content, lower muscle mass, and higher fat-to-muscle ratio were associated with better cognitive performance and lower risk of all-cause dementia in elderly participants, especially in males [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Alzheimer Disease Pathology and Neurodegeneration in Midlife Obesity: A Pilot Study

2024

Aging dis

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Obesity and excess adiposity at midlife are risk factors for Alzheimer disease (AD). Visceral fat is known to be associated with insulin resistance and a pro-inflammatory state, the two mechanisms involved in AD pathology. We assessed the association of obesity, MRI-determined abdominal adipose tissue volumes, and insulin resistance with PET-determined amyloid and tau uptake in default mode network areas, and MRIdetermined brain volume and cortical thickness in AD cortical signature in the cognitively normal midlife population. Thirty-two middle-aged (age: 51.27±6.12 years, 15 males, body mass index (BMI): 32.28±6.39 kg/m2) cognitively normal participants, underwent bloodwork, brain and abdominal MRI, and amyloid and tau PET scan. Visceral and subcutaneous adipose tissue (VAT, SAT) were semi-automatically segmented using VOXel Analysis Suite (Voxa). FreeSurfer was used to automatically segment brain regions using a probabilistic atlas. PET scans were acquired using [11C]PiB and AV-1451 tracers and were analyzed using PET unified pipeline. The association of brain volumes, cortical thicknesses, and PiB and AV-1451 standardized uptake value ratios (SUVRs) with BMI, VAT/SAT ratio, and insulin resistance were assessed using Spearman's partial correlation. VAT/SAT ratio was associated significantly with PiB SUVRs in the right precuneus cortex (p=0.034) overall, controlling for sex. This association was significant only in males (p=0.044), not females (p=0.166). Higher VAT/SAT ratio and PiB SUVRs in the right precuneus cortex were associated with lower cortical thickness in AD-signature areas predominantly including bilateral temporal cortices, parahippocampal, medial orbitofrontal, and cingulate cortices, with age and sex as covariates. Also, higher BMI and insulin resistance were associated with lower cortical thickness in bilateral temporal poles. In midlife cognitively normal adults, we demonstrated higher amyloid pathology in the right precuneus cortex in individuals with a higher VAT/SAT ratio, a marker of visceral obesity, along with a lower cortical thickness in AD-signature areas associated with higher visceral obesity, insulin resistance, and amyloid pathology.

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Plasma Alzheimer's disease biomarker variability: Amyloid‐independent and amyloid‐dependent factors

Lee,

Kang,

Shin

et al. 2024

Alzheimer's & Dementia

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INTRODUCTIONWe aimed to investigate which factors affect plasma biomarker levels via amyloid beta (Aβ)‐independent or Aβ‐dependent effects and improve the predictive performance of these biomarkers for Aβ positivity on positron emission tomography (PET).METHODSA total of 2935 participants underwent blood sampling for measurements of plasma Aβ42/40 ratio, phosphorylated tau 217 (p‐tau217; ALZpath), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) levels using single‐molecule array and Aβ PET. Laboratory findings were collected using a routine blood test battery.RESULTSAβ‐independent factors included hemoglobin and estimated glomerular filtration rate (eGFR) for p‐tau217 and hemoglobin, eGFR, and triiodothyronine (T3) for GFAP and NfL. Aβ‐dependent factors included apolipoprotein E genotypes, body mass index status for Aβ42/40, p‐tau217, GFAP, and NfL. However, these factors exhibited negligible or modest effects on Aβ positivity on PET.DISCUSSIONOur findings highlight the importance of accurately interpreting plasma biomarkers for predicting Aβ uptake in real‐world settings.Highlights We investigated factor–Alzheimer's disease plasma biomarker associations in a large Korean cohort. Hemoglobin and estimated glomerular filtration rate affect the biomarkers independently of brain amyloid beta (Aβ). Apolipoprotein E genotypes and body mass index status affect the biomarkers dependent on brain Aβ. Addition of Aβ‐independent factors shows negligible effect in predicting Aβ positivity. Adjusting for Aβ‐dependent factors shows a modest effect in predicting Aβ positivity.

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Association of late-life body mass index with the risk of Alzheimer disease: a 10-year nationwide population-based cohort study

Cited by 5 publications

References 41 publications

Review of the determinants contributing to the demographics of Alzheimer’s syndrome: Prevention techniques, risk factors, and insights for public health

Review of the determinants contributing to the demographics of Alzheimer’s syndrome: Prevention techniques, risk factors, and insights for public health

Alzheimer Disease Pathology and Neurodegeneration in Midlife Obesity: A Pilot Study

Plasma Alzheimer's disease biomarker variability: Amyloid‐independent and amyloid‐dependent factors

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