Dataset Information

Alzheimer disease biomarkers are associated with body mass index.

ABSTRACT:

Objective

Both low and high body mass index (BMI) has been associated with cognitive impairment and dementia risk, including Alzheimer disease (AD). We examined the relationship of BMI with potential underlying biological substrates for cognitive impairment.

Methods

We analyzed cross-sectional data from participants enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) with PET imaging using Pittsburgh Compound B (PiB, n = 101) or CSF analyses (n = 405) for ?-amyloid peptide (A?) and total tau. We assessed the relationship of CSF biomarkers and global PiB uptake with BMI using linear regression controlling for age and sex. We also assessed BMI differences between those who were and were not considered biomarker positive. Finally, we assessed BMI change over 2 years in relationship to AD biomarkers.

Results

No dementia, mild cognitive impairment (MCI), and AD groups were not different in age, education, or BMI. In the overall sample, CSF A? (? = 0.181, p < 0.001), tau (? = -0.179, p < 0.001), tau/A? ratio (? = -0.180, p < 0.001), and global PiB uptake (? = -0.272, p = 0.005) were associated with BMI, with markers of increased AD burden associated with lower BMI. Fewer overweight individuals had biomarker levels indicative of pathophysiology (p < 0.01). These relationships were strongest in the MCI and no dementia groups.

Conclusions

The presence and burden of in vivo biomarkers of cerebral amyloid and tau are associated with lower BMI in cognitively normal and MCI individuals. This supports previous findings of systemic change in the earliest phases of the disease. Further, MCI in those who are overweight may be more likely to result from heterogeneous pathophysiology.

SUBMITTER: Vidoni ED

PROVIDER: S-EPMC3233188 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Alzheimer disease biomarkers are associated with body mass index.

Vidoni E D ED Townley R A RA Honea R A RA Burns J M JM

Neurology 20111101 21

<h4>Objective</h4>Both low and high body mass index (BMI) has been associated with cognitive impairment and dementia risk, including Alzheimer disease (AD). We examined the relationship of BMI with potential underlying biological substrates for cognitive impairment.<h4>Methods</h4>We analyzed cross-sectional data from participants enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) with PET imaging using Pittsburgh Compound B (PiB, n = 101) or CSF analyses (n = 405) for β-amyloid ...[more]

PMID: 22105948

Similar Datasets

Project description:AimsThere are limited data examining whether body mass index (BMI) influences the association between cardiovascular biomarkers and incident heart failure (HF).Methods and resultsThirteen biomarkers representing key HF domains were measured: N-terminal pro-B-type natriuretic peptide (NT-proBNP), mid-regional pro-A-type natriuretic peptide (MR-proANP), cardiac troponin T (cTnT), C-reactive protein, procalcitonin, galectin-3, C-terminal pro-endothelin-1 (CT-proET-1), mid-regional pro-adrenomedullin, plasminogen activator inhibitor-1, copeptin, renin, aldosterone, and cystatin-C. Associations of biomarkers with BMI were examined using linear regression models, and with incident HF using Cox regression models. We selected biomarkers significantly associated with incident HF, and evaluated whether BMI modified these associations. Among 8202 individuals, 41% were overweight (BMI 25-30 kg/m2 ), and 16% were obese (BMI ≥30 kg/m2 ). Mean age of the cohort was 49 years (range 28-75), and 50% were women. All biomarkers except renin were associated with BMI: inverse associations were observed with NT-proBNP, MR-proANP, CT-proET-1 and aldosterone whereas positive associations were observed with the remaining biomarkers (all P ≤ 0.001). During 11.3 ± 3.1 years of follow-up, 357 HF events were recorded. Only NT-proBNP, MR-proANP and cTnT remained associated with incident HF (P < 0.001), and a significant biomarker*BMI interaction was not observed (interaction P > 0.1). Combined NT-proBNP and cTnT measurements modestly improved performance metrics of the clinical HF model in overweight (ΔC-statistic = 0.024; likelihood ratio χ2 = 38; P < 0.001) and obese (ΔC-statistic = 0.020; likelihood ratio χ2 = 32; P < 0.001) individuals.ConclusionsPlasma concentrations of several cardiovascular biomarkers are influenced by obesity. Only NT-proBNP, MR-proANP and cTnT were associated with incident HF, and BMI did not modify these associations. A combination of NT-proBNP and cTnT improves HF risk prediction in overweight and obese individuals.

Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.

Project description:BackgroundDNA methylation is associated with body mass index (BMI), but it is not clear if methylation scores are biomarkers for extant BMI or predictive of future BMI. Here, we explore the causal nature and predictive utility of DNA methylation measured in peripheral blood with BMI and cardiometabolic traits.MethodsAnalyses were conducted across the life course using the ARIES cohort of mothers (n = 792) and children (n = 906), for whom DNA methylation and genetic profiles and BMI at multiple time points (3 in children at birth, in childhood and in adolescence; 2 in mothers during pregnancy and in middle age) were available. Genetic and DNA methylation scores for BMI were derived using published associations between BMI and DNA methylation and genotype. Causal relationships between methylation and BMI were assessed using Mendelian randomisation and cross-lagged models.ResultsThe DNA methylation scores in adult women explained 10% of extant BMI variance. However, less extant variance was explained by scores generated in the same women during pregnancy (2% BMI variance) and in older children (15-17 years; 3% BMI variance). Similarly, little extant variance was explained in younger children (at birth and at 7 years; 1% and 2%, respectively). These associations remained following adjustment for smoking exposure and education levels. The DNA methylation score was found to be a poor predictor of future BMI using linear and cross-lagged models, suggesting that DNA methylation variation does not cause later variation in BMI. However, there was some evidence to suggest that BMI is predictive of later DNA methylation. Mendelian randomisation analyses also support this direction of effect, although evidence is weak. Finally, we find that DNA methylation scores for BMI are associated with extant cardiometabolic traits independently of BMI and genetic score.ConclusionThe age-specific nature of DNA methylation associations with BMI, lack of causal relationship and limited predictive ability of future BMI indicate that DNA methylation is likely influenced by BMI and might more accurately be considered a biomarker of BMI and related outcomes rather than a predictor. Future epigenome-wide association studies may benefit from further examining associations between early DNA methylation and later health outcomes.

Dataset Information

Alzheimer disease biomarkers are associated with body mass index.

Objective

Methods

Results

Conclusions

Publications

Alzheimer disease biomarkers are associated with body mass index.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets