Body height in young adult men and risk of dementia later in adult life

Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

Propensity Scores in Health Disparities Research: The Example of Cognitive Aging and the Hispanic Paradox

BACKGROUND

Individuals of Mexican ancestry in the United States experience substantial socioeconomic disadvantages compared with non-Hispanic white individuals; however, some studies show these groups have similar dementia risk. Evaluating whether migration selection factors (e.g., education) associated with risk of Alzheimer disease and related dementia (ADRD) explain this paradoxical finding presents statistical challenges. Intercorrelation of risk factors, common with social determinants, could make certain covariate patterns very likely or unlikely to occur for particular groups, which complicates their comparison. Propensity score (PS) methods could be leveraged here to diagnose nonoverlap and help balance exposure groups.

METHODS

We compare conventional and PS-based methods to examine differences in cognitive trajectories between foreign-born Mexican American, US-born Mexican American, and US-born non-Hispanic white individuals in the Health and Retirement Study (1994-2018). We examined cognition using a global measure. We estimated trajectories of cognitive decline from linear mixed models adjusted for migration selection factors also associated with ADRD risk conventionally or with inverse probability weighting. We also employed PS trimming and match weighting.

RESULTS

In the full sample, where PS overlap was poor, unadjusted analyses showed both Mexican ancestry groups had worse baseline cognitive scores but similar or slower rates of decline compared with non-Hispanic white adults; adjusted findings were similar, regardless of method. Focusing analyses on populations where PS overlap was improved (PS trimming and match weighting) did not alter conclusions.

CONCLUSIONS

Attempting to equalize groups on migration selection and ADRD risk factors did not explain paradoxical findings for Mexican ancestry groups in our study.

Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data

Mendelian randomization (MR) has been increasingly applied for causal inference with observational data by using genetic variants as instrumental variables (IVs). However, the current practice of MR has been largely restricted to investigating the total causal effect between two traits, while it would be useful to infer the direct causal effect between any two of many traits (by accounting for indirect or mediating effects through other traits). For this purpose we propose a two-step approach: we first apply an extended MR method to infer (i.e. both estimate and test) a causal network of total effects among multiple traits, then we modify a graph deconvolution algorithm to infer the corresponding network of direct effects. Simulation studies showed much better performance of our proposed method than existing ones. We applied the method to 17 large-scale GWAS summary datasets (with median N = 256879 and median #IVs = 48) to infer the causal networks of both total and direct effects among 11 common cardiometabolic risk factors, 4 cardiometabolic diseases (coronary artery disease, stroke, type 2 diabetes, atrial fibrillation), Alzheimer's disease and asthma, identifying some interesting causal pathways. We also provide an R Shiny app (https://zhaotongl.shinyapps.io/cMLgraph/) for users to explore any subset of the 17 traits of interest.

Poor Cognitive Agility Conservation in Obese Aging People

Life expectancy has been boosted in recent decades at expenses of increasing the age-associated diseases. Dementia, for its incidence, stands out among the pathologies associated with aging. The exacerbated cognitive deterioration disables people from carrying out their daily lives autonomously and this incidence increases exponentially after 65 years of age. The etiology of dementia is a miscellaneous combination of risk factors that restrain the quality of life of our elderly. In this sense, it has been established that some metabolic pathologies such as obesity and diabetes act as a risk factor for dementia development. In contrast, a high educational level, as well as moderate physical activity, have been shown to be protective factors against cognitive impairment and the development of dementia. In the present study, we have evaluated the metabolic composition of a population between 60-90 years old, mentally healthy and with high academic degrees. After assessing agility in mental state, we have established relationships between their cognitive abilities and their body composition. Our data support that excess body fat is associated with poorer maintenance of cognition, while higher percentages of muscle mass are associated with the best results in the cognitive tests.

Height and nigral neuron density in Parkinson's disease

Background

The dopaminergic system modulates growth hormone secretion and previous results have suggested a link between short stature and an increased risk of Parkinson’s disease (PD).

Methods

In 36 Lewy body spectrum disease (LBD) cases (PD = 22) and 19 controls, nigral TH-positive neuron densities were measured postmortem from midbrain sections and corrected with the Abercrombie method. Body measurements were collected from autopsies or patient records. Our aim was to investigate the possible relationship between height and the density of neurons in the substantia nigra pars compacta (SNc).

Results

SNc neuron density (n/mm²) had an inverse association with height, (R² = 0.317, p < 0.0001) in patients. The association was not explained by weight, age, sex, brain weight, medication, or disease motor severity. The association was also separately observed in patients with PD (n = 22), but not in subjects who died without diagnosed neurological diseases.

Conclusions

Individual adult height may be connected to nigral neuron numbers in patients with LBDs, including PD.

Sex-related associations between body height and cognitive impairment among low-income elderly adults in rural China: a population-based cross-sectional study

BACKGROUND

Body height is a marker of childhood health and cumulative net nutrition during growth periods. However, sex-specific associations between body height and cognitive impairment are not well known in northern rural China.

METHODS

We assessed sex differences in the association between body height and cognitive impairment in a low-income elderly population in rural China. A population-based cross-sectional study was conducted from April 2014 to August 2014 to collect basic information from elderly residents aged 60 years and older in rural areas of Tianjin, China. Body height and Mini Mental State Examination (MMSE) scores were measured, and the relationships between these variables were assessed.

RESULTS

A total of 1081 residents with a mean age of 67.7 years were enrolled in this study. After adjusting for age, educational attainment, smoking status, drinking status, and the presence of hypertension, diabetes, and hypercholesterolemia, higher body height was found to be associated with a decreased prevalence of cognitive impairment in elderly men. Each 1-dm increase in height was associated with a 37% decrease in the prevalence of cognitive impairment. However, there was no significant association between body height and cognitive impairment among elderly women.

CONCLUSION

In conclusion, shorter body height was related to cognitive impairment independently of age, educational attainment, lifestyle factors, and health-related comorbid factors among low-income elderly men in rural China. Accordingly, shorter elderly men may be targeted for effective dementia prevention in rural China.

Heterogeneous effects of genetic risk for Alzheimer's disease on the phenome

Here we report how four major forms of Alzheimer's disease (AD) genetic risk-APOE-ε4, APOE-ε2, polygenic risk and familial risk-are associated with 273 traits in ~500,000 individuals in the UK Biobank. The traits cover blood biochemistry and cell traits, metabolic and general health, psychosocial health, and cognitive function. The difference in the profile of traits associated with the different forms of AD risk is striking and may contribute to heterogenous presentation of the disease. However, we also identify traits significantly associated with multiple forms of AD genetic risk, as well as traits showing significant changes across ages in those at high risk of AD, which may point to their potential roles in AD etiology. Finally, we highlight how survivor effects, in particular those relating to shared risks of cardiovascular disease and AD, can generate associations that may mislead interpretation in epidemiological AD studies. The UK Biobank provides a unique opportunity to powerfully compare the effects of different forms of AD genetic risk on the phenome in the same cohort.

Taller adult height is associated with better performance of cognitive trajectories in Chinese over 45 years old: Evidence from the China Health and Retirement Longitudinal Study

AIM

The association between adult height and follow-up cognition requires an update in China. We aimed to examine the association between baseline height and follow-up cognitive trajectories in Chinese subjects from the China Health and Retirement Longitudinal Study (CHARLS).

METHODS

A total of 6508 adults aged 45 years or older from the CHARLS were included for analysis. Latent class growth modeling was used to determine cognitive trajectories of 2011, 2013 and 2015. Multivariable linear regression and logistic regression models were used to examine the association between baseline adult height and cognitive performance and trajectories, respectively.

RESULTS

At baseline, an increment of 1 SD (8.3 cm) of height was associated with a higher global cognitive score (β = 0.492, 95% CI, 0.348-0.636), verbal episodic memory (β = 0.155, 95% CI, 0.086-0.224) and mental status (β = 0.337, 95% CI, 0.225-0.449). These associations were still observed even when stratified by sex. Prospectively, for females, the third quartile of height level (i.e., 155 to 158 cm) was associated with a better global cognitive function trajectory (OR = 1.627, P = 0.001, P for trend = 0.009) and mental status trajectory (OR = 1.456, P = 0.012, P for trend = 0.047); and the tallest height level (i.e., 159 cm or taller) was related to a better verbal episodic memory trajectory (OR = 1.574, P = 0.017). For males, no associations were observed.

CONCLUSION

Increased stature might be associated with better cognitive trajectories for subjects in China. Geriatr Gerontol Int 2021; 21: 732-740.

Association of life course socioeconomic status and adult height with cognitive functioning of older adults in India and China

BACKGROUND

Cognitive functioning is an important measure of intrinsic capacity. In this study, we examine the association of life course socioeconomic status (SES) and height with cognitive functioning among older adults (50+) in India and China. The age pattern of cognitive functioning with measures of life course socioeconomic status has also been examined.

METHODS

Cross-sectional comparative analysis was conducted using the WHO's Study on global AGEing and adult health (SAGE) data for India and China. Multilevel mixed-effect linear regression analysis was used to examine the association of life course socioeconomic status and adult height with cognitive functioning.

RESULTS

In both India and China, parental education as a measure of childhood socioeconomic status was positively associated with cognitive functioning. The association between adult socioeconomic status and cognitive functioning was positive and significant. Height was significantly and positively associated with improved cognitive functioning of older adults in India and China. Furthermore, the age-related decline in cognitive functioning score was higher among older adults whose parents had no schooling, particularly in China. The cognitive functioning score with age was much lower among less-educated older adults than those with higher levels of education in China. Wealthier older adults in India had higher cognitive functioning in middle ages, however, wealth differences narrowed with age.

CONCLUSIONS

The results of this study suggest a significant association of lifetime socioeconomic status and cumulative net nutrition on later-life cognitive functioning in middle-income settings.