Explore the vast range of titles available.

Type 2 Diabetes Mellitus (henceforth diabetes) affects roughly 35 million individuals in the US and is a major risk factor for cardiovascular and kidney disease. Serum Cystatin-C is used to monitor renal function and detect kidney damage. Recent research has focused on linking Cystatin-C to cardiovascular risk and disease, but most findings focus on small sample sizes and generalize poorly to diverse populations, thus limiting epidemiological inferences. The aim of this manuscript is to study the association between Cystatin-C, diabetes, and mortality and test for possible sex or racial/ethnic background modifications in these relationships. We analyzed 8-years of biennial panel data from Health and Retirement Study participants 50-years and older who self-identified as White (unweighted N (uN) = 5,595), Black (uN = 867), or Latino (uN = 565) for a total of uN = 7,027 individuals. We modeled diabetes and death over 8-years as function of baseline Cystatin-C (log transformed) adjusting for covariates and tested modifications in associations by race/ethnic background and sex. Mean log Cystatin-C at visit 1 was 0.03±0.32 standard deviation. A 10% increase in Cystatin-C levels was associated with 13% increased relative risk of diabetes at baseline (11% and 9% by years 4 and 8). A 10% increase in Cystatin-C was highly associated with increased relative risk of death (28% and 31% by years 4 and 8). These associations were present even after adjusting for possible confounders and were not modified by sex or racial/ethnic background. Despite differential risks for diabetes and mortality by racial/ethnic groups, Cystatin-C was equally predictive of these outcomes across groups. Cystatin-C dysregulations could be used as a risk indicator for diabetes and as a warning sign for accelerated risk of mortality.

Sleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. Using data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we apply principal component analysis (PCA) to seven SDB-related measures. We estimate the associations of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint penalized regression analysis. The discovery analysis includes 3299 individuals, with validation in a separate dataset of 1522 individuals. Five metabolite associations with SDB PCs are discovered and replicated. SDB PC1, characterized by frequent respiratory events common in older and male adults, is associated with pregnanolone and progesterone-related sulfated metabolites. SDB PC2, characterized by short respiratory event length and self-reported restless sleep, enriched in young adults, is associated with sphingomyelins. Metabolite risk scores (MRSs), representing metabolite signatures associated with the two SDB PCs, are associated with 6-year incident hypertension and diabetes. These MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions. Sleep-disordered breathing (SDB) is a prevalent disorder linked to higher cardiovascular disease risk. Here, the authors show that summary scores reflecting SDB metabolite signatures are associated with increased risks for incident hypertension and diabetes, potentially useful in guiding risk stratification.

Limited research exists on COVID-19 associated brain fog, and on the long-term cognitive and psychiatric sequelae in racially and ethnically diverse patients. We characterize the neuropsychological sequelae of post-acute COVID-19 in a diverse cohort and investigate whether COVID-19 clinical severity remains associated with brain fog and cognitive deficits approximately 2 years post infection. A cross-sectional study of patients with a history of COVID-19 hospitalization (March-September 2020). COVID-19 clinical severity was indexed using the National Early Warning Score 2 and a comprehensive neuropsychological tele-battery was administered 2 years post discharge. Pearson's r correlations assessed association, while independent sample t-tests examined group differences. Significant outcomes were further analyzed using multiple regression and ANCOVAs, adjusting for key covariates. In 41 adult patients (19 female, 30 Hispanic, 13 Black, mean age of 65 (SD = 15), COVID-19 level of severity was associated with greater number of endorsed brain fog symptoms (Pearson's r = .34, 95% CI [.04, .59]), worse overall cognitive functioning (global cognition: r = -.36, 95% CI [-.61, -.05]) and reduced performance on an attention and working memory task (digit span backwards: r = -.41, 95% CI [-.66, -.09]) at 2-year follow-up. Brain fog symptoms most associated with COVID-19 severity included difficulty focusing (r = .46, 95% CI [.18, .67]), detached (r = .41, 95% CI [.12, .64]) and feeling sleepy (r = .40, 95% CI [.11, .63]). Patients' cognitive performance was generally below average (global cognition z-score: M = -.96, SD = .66), with group differences based on sex and ethnicity evidenced on individual cognitive tests. This study emphasizes the importance of continued research on the long-term effects of COVID-19 infection on neuropsychological outcomes, particularly among underrepresented, health-disparate groups. Greater understanding of these associations could improve detection and treatment of those at increased risk of cognitive decline or impairment.

To describe sleep characteristics of shift workers compared with day workers from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sueño ancillary study and test the hypothesis that shift work is associated with shorter sleep duration, worse sleep quality, greater sleep variability, and other sleep/health-related factors. Employed adults (N = 1253, mean age 46.3 years, 36.3% male) from the Sueño study were included. Measures of sleep duration, timing, regularity, and continuity were calculated from 7 days of wrist-activity monitoring. Participants provided information on demographics, employment, work schedule (day, afternoon, night, split, irregular, and rotating), sleepiness, depressive symptoms, medications, caffeine, and alcohol use. Survey linear regression adjusting for age, sex, background, site, number of jobs, and work hours was used. In age and sex-adjusted models, all shift work schedules were associated with delayed sleep timing. Night and irregular schedules were associated with shorter sleep duration, greater napping, and greater variability of sleep. Afternoon and rotating shifts were associated with lower sleep regularity. In fully adjusted models, night and irregular schedules remained associated with shorter sleep duration, later sleep midpoint, and greater variability in sleep measures compared with day schedules. Split schedules were associated with, less time in bed, less sleep fragmentation, and less wake during the sleep period than day schedules. Work schedule significantly affects sleep-wake with substantial differences between day work and other types of schedule. Detailed assessment of work schedule type not just night shift should be considered as an important covariate when examining the association between sleep and health outcomes.

Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. Studying metabolomic associations with OSA in a diverse community-based cohort may provide insights into the pathophysiology of OSA. We aimed to develop and replicate a metabolite index for OSA and identify individual metabolites associated with OSA. We studied 219 metabolites and their associations with the apnea hypopnea index (AHI) and with moderate-severe OSA (AHI ≥ 15) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n = 3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites jointly associated with OSA, which was used to develop a metabolite index for OSA. Results were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) (n = 475). When assessing the associations with individual metabolites, we identified seven metabolites significantly positively associated with OSA in HCHS/SOL (FDR p  < 0.05), of which four associations—glutamate, oleoyl-linoleoyl-glycerol (18:1/18:2), linoleoyl-linoleoyl-glycerol (18:2/18:2) and phenylalanine, were replicated in MESA (one sided- p  < 0.05). The OSA metabolite index, composed of 14 metabolites, was associated with a 50% increased risk for moderate-severe OSA (OR = 1.50 [95% CI 1.21–1.85] per 1 SD of OSA metabolite index, p  < 0.001) in HCHS/SOL and 55% increased risk (OR = 1.55 [95% CI 1.10–2.20] per 1 SD of OSA metabolite index, p  = 0.013) in MESA, both adjusted for demographics, lifestyle, and comorbidities. Similar albeit less significant associations were observed for AHI. Replication of the metabolite index in an independent multi-ethnic dataset demonstrates the robustness of metabolomic-based OSA index to population heterogeneity. Replicated metabolite associations may provide insights into OSA-related molecular and metabolic mechanisms.

Applying causal inference methods, such as weighting and matching methods, to a survey sampled population requires properly incorporating the survey weights and design to obtain effect estimates that are representative of the target population and correct standard errors (SEs). With a simulation study, we compared various approaches for incorporating the survey weights and design into weighting and matching-based causal inference methods. When the models were correctly specified, most approaches performed well. However, when a variable was treated as an unmeasured confounder and the survey weights were constructed to depend on this variable, only the matching methods that used the survey weights in causal estimation and as a covariate in matching continued to perform well. If unmeasured confounders are potentially associated with the survey sample design, we recommend that investigators include the survey weights as a covariate in matching, in addition to incorporating them in causal effect estimation. Finally, we applied the various approaches to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and found that insomnia has a causal association with both mild cognitive impairment (MCI) and incident hypertension 6–7 years later in the US Hispanic/Latino population.

ABSTRACTObjectivesFrailty is associated with cognitive decline in older adults. However, the mechanisms explaining this relationship are poorly understood. We hypothesized that sleep quality may mediate the relationship between frailty and cognition. Participants154 participants aged between 50-90 years (mean = 69.1 years, SD = 9.2 years) from the McKnight Brain Registry were included. MeasurementsParticipants underwent a full neuropsychological evaluation, frailty and subjective sleep quality assessments. Direct relationships between frailty and cognitive function were assessed using linear regression models. Statistical mediation of these relationships by sleep quality was assessed using nonparametric bootstrapping procedures. ResultsFrailty severity predicted weaker executive function (B = −2.77, β = −0.30, 95% CI = −4.05 – −1.29) and processing speed (B = −1.57, β = −0.17, 95% CI = −3.10 – −0.16). Poor sleep quality predicted poorer executive function (B = −0.47, β = −0.21, 95% CI = −0.79 – −0.08), processing speed (B = −0.64, β = −0.28, 95% CI = −0.98 – −0.31), learning (B = −0.42, β = −0.19, 95% CI = −0.76 – −0.05) and delayed recall (B = −0.41, β = −0.16, 95% CI = −0.80 – −0.31). Poor sleep quality mediated the relationships between frailty severity and executive function (B = −0.66, β = −0.07, 95% CI = −1.48 – −0.39), learning (B = −0.85, β = −0.07, 95% CI = −1.85 – −0.12), delayed recall (B = −0.47, β = −0.08, 95% CI = −2.12 – −0.39) and processing speed (B = −0.90, β = −0.09, 95% CI = −1.85 – −0.20). ConclusionsRelationships between frailty severity and several cognitive outcomes were significantly mediated by poor sleep quality. Interventions to improve sleep quality may be promising avenues to prevent cognitive decline in frail older adults.

Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 × 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.

Cardiovascular disease (CVD) risk factors are highly prevalent among Hispanic/Latino adults, while the prevalence of MRI infarcts is not well-documented. We, therefore, sought to examine the relationships between CVD risk factors and infarcts with brain structure among Hispanic/Latino individuals. Participants included 1,886 Hispanic/Latino adults (50-85 years) who underwent magnetic resonance imaging (MRI) as part of the Study of Latinos-Investigation of Neurocognitive Aging-MRI (SOL-INCA-MRI) study. CVD risk was measured approximately 10.5 years before MRI using the Framingham cardiovascular risk score, a measure of 10-year CVD risk (low (<10%), medium (10- < 20%), and high (≥20%)). MR infarcts were determined as present or absent. Outcomes included total brain, cerebral and lobar cortical gray matter, hippocampal, lateral ventricle, and total white matter hyperintensity (WMH) volumes. Linear regression models tested associations between CVD risk and infarct with MRI outcomes and for modifications by age and sex. Sixty percent of participants were at medium or high CVD risk. Medium and high CVD risk were associated with lower total brain and frontal gray matter and higher WMH volumes compared to those with low CVD risk. High CVD risk was additionally associated with lower total cortical gray matter and parietal volumes and larger lateral ventricle volumes. Men tended to have greater CVDRF-related differences in total brain volumes than women. The association of CVD risk factors on total brain volumes increased with age, equal to an approximate 7-year increase in total brain aging among the high-CVD-risk group compared to the low-risk group. The presence of infarct(s) was associated with lower total brain volumes, which was equal to an approximate 5-year increase in brain aging compared to individuals without infarcts. Infarcts were also associated with smaller total cortical gray matter, frontal and parietal volumes, and larger lateral ventricle and WMH volumes. The high prevalence of CVD risk among Hispanic/Latino adults may be associated with accelerated brain aging.

Background Blood-based biomarkers hold significant promise for the early detection and diagnosis of Alzheimer’s disease (AD) and other dementias. Age-related changes in blood levels of AD biomarkers are well-documented but poorly understood. Epigenetic clocks are mathematical models based on DNA methylation patterns that reflect various aspects of the multidimensional aging process. We investigated the associations of epigenetic aging with five blood-based AD biomarkers in 2656 Hispanic/Latino adults (mean age 62.5 years; 65% females) from the Hispanic Community Health Study/Study of Latinos. We used multivariable linear regression models to estimate the associations of acceleration in each of five epigenetic clocks with each biomarker in the total sample and in sex-specific strata, controlling for chronological age, sex (except in sex-stratified analyses), Hispanic/Latino background, recruitment site, risk factors, and comorbid medical conditions. Results There were varying strengths of association between acceleration of the clocks and the plasma biomarkers. There were significant associations of acceleration in all epigenetic clocks with higher plasma levels of neurofilament light chain (NfL) (Beta = 0.0045 to 0.0193; P  = 0.022 to 4.9 × 10 –15 ). There were significant associations of acceleration in all epigenetic clocks except DunedinPACE with higher plasma levels of amyloid beta (Aβ)40 (Beta = 0.0033 to 0.0049; P  = 0.024 to 1.7 × 10 –5 ). PC-PhenoAge acceleration was associated with all circulating biomarkers but its associations with Aβ42, Aβ42/40 ratio, and phosphorylated Tau 181 (p-Tau181) showed heterogeneity by sex. Specifically, PC-PhenoAge acceleration was associated with higher Aβ42 and p-Tau181 levels in males (Beta = 0.0066, P  = 0.002 and Beta = 0.0158, P  = 2 × 10 –4 , respectively) but not females, while it was associated with lower Aβ42/40 ratio in females (Beta = − 0.0032, P  = 0.012) but not males. Conclusions Epigenetic age acceleration is associated with circulating biomarkers of AD in Hispanic/Latino adults. The second‐generation clock PC-PhenoAge showed strong and consistent associations across all biomarkers, and thus may reflect biological processes most relevant to age-related changes in AD biomarkers. Considering sex differences in the relationship between biological aging and circulating AD biomarkers is paramount.