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      BMI and Allostatic Load Are Directly Associated with Longitudinal Increase in Plasma Neurofilament Light among Urban Middle-Aged Adults

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          ABSTRACT

          Background

          Plasma neurofilament light chain (NfL) is a novel biomarker for age-related neurodegenerative disease. We tested whether NfL may be linked to cardiometabolic risk factors, including BMI, the allostatic load (AL) total score (ALtotal), and related AL continuous components (ALcomp). We also tested whether these relations may differ by sex or by race.

          Methods

          We used data from the HANDLS (Healthy Aging in Neighborhoods of Diversity across the Life Span) study [n = 608, age at visit 1 (v1: 2004–2009): 30–66 y, 42% male, 58% African American] to investigate associations of initial cardiometabolic risk factors and time-dependent plasma NfL concentrations over 3 visits (2004–2017; mean ± SD follow-up time: 7.72 ± 1.28 y), with outcomes being NfLv1 and annualized change in NfL (δNfL). We used mixed-effects linear regression and structural equations modeling (SM).

          Results

          BMI was associated with lower initial (γ01 = −0.014 ± 0.002, P < 0.001) but faster increase in plasma NfL over time (γ11 = +0.0012 ± 0.0003, P < 0.001), a pattern replicated for ALtotal. High-sensitivity C-reactive protein (hsCRP), serum total cholesterol, and resting heart rate at v1 were linked with faster plasma NfL increase over time, overall, while being uncorrelated with NfLv1 (e.g., hsCRP × Time, full model: γ11 = +0.004 ± 0.002, P = 0.015). In SM analyses, BMI's association with δNfL was significantly mediated through ALtotal among women [total effect (TE) = +0.0014 ± 0.00038, P < 0.001; indirect effect = +0.00042 ± 0.00019, P = 0.025; mediation proportion = 30%], with only a direct effect (DE) detected among African American adults (TE = +0.0011 ± 0.0004, P = 0.015; DE = +0.0010 ± 0.00048, P = 0.034). The positive associations between ALtotal/BMI and δNfL were mediated through increased glycated hemoglobin (HbA1c) concentrations, overall.

          Conclusions

          Cardiometabolic risk factors, particularly elevated HbA1c, should be screened and targeted for neurodegenerative disease, pending comparable longitudinal studies. Other studies examining the clinical utility of plasma NfL as a neurodegeneration marker should account for confounding effects of BMI and AL.

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          Most cited references66

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          The obesity epidemic in the United States--gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis.

          This review of the obesity epidemic provides a comprehensive description of the current situation, time trends, and disparities across gender, age, socioeconomic status, racial/ethnic groups, and geographic regions in the United States based on national data. The authors searched studies published between 1990 and 2006. Adult overweight and obesity were defined by using body mass index (weight (kg)/height (m)(2)) cutpoints of 25 and 30, respectively; childhood "at risk for overweight" and overweight were defined as the 85th and 95th percentiles of body mass index. Average annual increase in and future projections for prevalence were estimated by using linear regression models. Among adults, obesity prevalence increased from 13% to 32% between the 1960s and 2004. Currently, 66% of adults are overweight or obese; 16% of children and adolescents are overweight and 34% are at risk of overweight. Minority and low-socioeconomic-status groups are disproportionately affected at all ages. Annual increases in prevalence ranged from 0.3 to 0.9 percentage points across groups. By 2015, 75% of adults will be overweight or obese, and 41% will be obese. In conclusion, obesity has increased at an alarming rate in the United States over the past three decades. The associations of obesity with gender, age, ethnicity, and socioeconomic status are complex and dynamic. Related population-based programs and policies are needed.
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            Neurofilaments as biomarkers in neurological disorders

            Neuroaxonal damage is the pathological substrate of permanent disability in various neurological disorders. Reliable quantification and longitudinal follow-up of such damage are important for assessing disease activity, monitoring treatment responses, facilitating treatment development and determining prognosis. The neurofilament proteins have promise in this context because their levels rise upon neuroaxonal damage not only in the cerebrospinal fluid (CSF) but also in blood, and they indicate neuroaxonal injury independent of causal pathways. First-generation (immunoblot) and second-generation (enzyme-linked immunosorbent assay) neurofilament assays had limited sensitivity. Third-generation (electrochemiluminescence) and particularly fourth-generation (single-molecule array) assays enable the reliable measurement of neurofilaments throughout the range of concentrations found in blood samples. This technological advancement has paved the way to investigate neurofilaments in a range of neurological disorders. Here, we review what is known about the structure and function of neurofilaments, discuss analytical aspects and knowledge of age-dependent normal ranges of neurofilaments and provide a comprehensive overview of studies on neurofilament light chain as a marker of axonal injury in different neurological disorders, including multiple sclerosis, neurodegenerative dementia, stroke, traumatic brain injury, amyotrophic lateral sclerosis and Parkinson disease. We also consider work needed to explore the value of this axonal damage marker in managing neurological diseases in daily practice.
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              Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease

              Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker.
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                Author and article information

                Contributors
                Journal
                The Journal of Nutrition
                Oxford University Press (OUP)
                0022-3166
                1541-6100
                February 2022
                February 08 2022
                October 29 2021
                February 2022
                February 08 2022
                October 29 2021
                : 152
                : 2
                : 535-549
                Affiliations
                [1 ]Laboratory of Epidemiology and Population Sciences, National Institute on Aging/NIH/Intramural Research Program, Baltimore, MD, USA
                [2 ]Department of Psychology, University of Maryland, Baltimore County, Catonsville, MD, USA
                [3 ]Department of Research Programs, Fort Belvoir Community Hospital, Fort Belvoir, VA, USA
                [4 ]Department of Demography, University of California, Berkeley, Berkeley, CA, USA
                Article
                10.1093/jn/nxab381
                34718678
                c1520646-3a04-47c0-ba16-12f44cec979b
                © 2021
                History

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