Kidney function is associated with plasma ATN biomarkers among Hispanics/Latinos: SOL-INCA and HCHS/SOL results
Bibliographic record
Abstract
Abstract Background Plasma amyloid-tau-neurodegeneration (ATN) biomarker levels may be influenced by non-brain systems, such as kidney function, which could impact the interpretation of ATN biomarker results, particularly in groups like Hispanic/Latino individuals with higher rates of cardiometabolic health issues. Here, we examine the association between kidney function and plasma ATN markers among a diverse sample of Hispanic/Latino individuals living in the U.S. Methods Data was collected from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL, Visit 1, 2008–2011), the largest prospective cohort study of noninstitutionalized Hispanic/Latino adults in the U.S., and its ancillary study, the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) which was conducted during the second visit of the parent HCHS/SOL study (Visit 2, 2015–2018). SOL-INCA aimed to examine the neurocognitive decline of middle-aged and older Hispanic/Latino adults, and the inclusion criteria were the age of 50-years and older by Visit 2 and completion of battery of neurocognitive tests at Visit 1. Survey linear regression models were used to examine associations between CKD status (estimated glomerular filtration rate [eGFR] < 60 ml/min/1.73m2 or urine albumin-creatinine ratio [uACR]) > = 30 mg/g) and the plasma ATN biomarkers (β-amyloid 42/40 ratio [Aβ42/40 ratio], phosphorylated-tau181 [p-Tau181], neurofilament light [NfL], and glial fibrillary associated protein [GFAP]), independently. All models adjusted for sociodemographic and cardiometabolic factors (BMI, diabetes, and hypertension). Results 5,968 participants were included in the study (mean age 63.4 ± 8.1, 54% women). CKD was associated with higher p-Tau181 (b = 0.82), NfL (b = 11.60) and GFAP levels (b = 31.41), and lower Aβ42/Aβ40 ratio (b=-0.004). Lower eGFR (i.e., reduced kidney function) was associated with higher p-Tau181, NfL, and GFAP levels (b ranges [-0.87 - -0.03]), and lower Aβ42/Aβ40 ratio (b = 0.000). Higher (natural log) uACR was associated with lower Aβ42/Aβ40 ratio and higher levels of all other biomarkers (b ranges [0.24–5.49]). Additionally, CKD, eGFR, and uACR were associated with ATN biomarkers in models adjusted for cardiometabolic risk factors, diabetes and hypertension. Conclusions CKD status, kidney function and urinary markers of kidney damage are significant confounders in the interpretation of plasma ATN biomarker levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".