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BACKGROUNDLeft ventricular hypertrophy (LVH) and dyslipidemia are strong, independent predictors for cardiovascular disease, but their relationship is less well studied. A longitudinal lipidomic profiling of left ventricular mass (LVM) and LVH is still lacking.METHODSUsing liquid chromatography-mass spectrometry (LC-MS), we repeatedly measured 1,542 lipids from 1,755 unique American Indians attending 2 exams (mean, 5 years apart). Cross-sectional associations of individual lipid species with LVM index (LVMI) were examined by generalized estimating equation (GEE), followed by replication in an independent biracial cohort (65% White, 35% Black). Baseline plasma lipids associated with LVH risk beyond traditional risk factors were identified by logistic GEE model in American Indians. Longitudinal associations between changes in lipids and changes in LVMI were examined by GEE, adjusting for baseline lipids, baseline LVMI, and covariates.RESULTSMultiple lipid species were significantly associated with LVMI or the risk of LVH in American Indians. Some lipids were confirmed in Black and White individuals. Moreover, some LVH-related lipids were inversely associated with risk of coronary heart disease (CHD). Longitudinal changes in several lipid species were significantly associated with changes in LVMI.CONCLUSIONAltered fasting plasma lipidome and its longitudinal change over time were significantly associated with LVMI and risk for LVH in American Indians. Our results offer insight into the role of individual lipid species in LV remodeling and risk of LVH, independent of known risk factors.FUNDINGThis study was supported by the NIH grant (R01DK107532). The Strong Heart Study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, NIH, Department of Health and Human Services, under contract nos. 75N92019D00027, 75N92019D00028, 75N92019D00029, and 75N92019D00030.

BACKGROUND: Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association. OBJECTIVES: This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD. METHODS: Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of

BACKGROUND: Dyslipidemia is an independent risk factor for coronary heart disease (CHD). Standard lipid panel cannot capture the complexity of the blood lipidome (ie, all molecular lipids in the blood). To date, very few large-scale epidemiological studies have assessed the full spectrum of the blood lipidome on risk of CHD, especially in a longitudinal setting. METHODS AND RESULTS: Using an untargeted liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species from 1835 unique American Indian participants who attended 2 clinical visits (≈5.5 years apart) and followed up to 17.8 years in the Strong Heart Family Study (SHFS). We first identified baseline lipid species associated with risk of CHD, followed by replication in a European population. The model adjusted for age, sex, body mass index, smoking, hypertension, diabetes, low-density lipoprotein cholesterol, estimated glomerular filtration rate, education, and physical activity at baseline. We then examined the longitudinal association between changes in lipid species and changes in cardiovascular risk factors during follow-up. Multiple testing was controlled by the false discovery rate. We found that baseline levels of multiple lipid species (eg, phosphatidylcholines, phosphatidylethanolamines, and ceramides) were associated with the risk of CHD and improved the prediction accuracy over conventional risk factors in American Indian people. Some identified lipids in American Indian people were replicated in European people. Longitudinal changes in multiple lipid species (eg, acylcarnitines, phosphatidylcholines, and triacylglycerols) were associated with changes in cardiovascular risk factors. CONCLUSIONS: Baseline plasma lipids and their longitudinal changes over time are associated with risk of CHD. These findings provide novel insights into the role of dyslipidemia in CHD.

BACKGROUND: Dyslipidemia is an important risk factor for hypertension and cardiovascular disease. Standard lipid panel cannot reflect the complexity of blood lipidome. The associations of individual lipid species with hypertension remain to be determined in large-scale epidemiological studies, especially in a longitudinal setting. METHODS: Using liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species in 3699 fasting plasma samples at 2 visits (1905 at baseline, 1794 at follow-up, ~5.5 years apart) from 1905 unique American Indians in the Strong Heart Family Study. We first identified baseline lipids associated with prevalent and incident hypertension, followed by replication of top hits in Europeans. We then conducted repeated measurement analysis to examine the associations of changes in lipid species with changes in systolic blood pressure, diastolic blood pressure, and mean arterial pressure. Network analysis was performed to identify lipid networks associated with the risk of hypertension. RESULTS: Baseline levels of multiple lipid species, for example, glycerophospholipids, cholesterol esters, sphingomyelins, glycerolipids, and fatty acids, were significantly associated with both prevalent and incident hypertension in American Indians. Some lipids were confirmed in Europeans. Longitudinal changes in multiple lipid species, for example, acylcarnitines, phosphatidylcholines, fatty acids, and triacylglycerols, were significantly associated with changes in blood pressure measurements. Network analysis identified distinct lipidomic patterns associated with the risk of hypertension. CONCLUSIONS: Baseline plasma lipid species and their longitudinal changes are significantly associated with hypertension development in American Indians. Our findings shed light on the role of dyslipidemia in hypertension and may offer potential opportunities for risk stratification and early prediction of hypertension.

Dyslipidemia is an independent and modifiable risk factor for aging and age-related disorders. Routine lipid panel cannot capture all individual lipid species in blood (i.e., blood lipidome). To date, a comprehensive assessment of the blood lipidome associated with mortality is lacking in large-scale community-dwelling individuals, especially in a longitudinal setting. Using liquid chromatograph-mass spectrometry, we repeatedly measured individual lipid species in 3,821 plasma samples collected at two visits (~ 5.5 years apart) from 1,930 unique American Indians in the Strong Heart Family Study. We first identified baseline lipids associated with risks for all-cause mortality and CVD mortality (mean follow-up period: 17.8 years) in American Indians, followed by replication of top hits in European Caucasians in the Malmö Diet and Cancer-Cardiovascular Cohort (n = 3,943, mean follow-up period: 23.7 years). The model adjusted age, sex, BMI, smoking, hypertension, diabetes, and LDL-c at baseline. We then examined the associations between changes in lipid species and risk of mortality. Multiple testing was controlled by false discovery rate (FDR). We found that baseline levels and longitudinal changes of multiple lipid species, e.g., cholesterol esters, glycerophospholipids, sphingomyelins, and triacylglycerols, were significantly associated with risks of all-cause or CVD mortality. Many lipids identified in American Indians could be replicated in European Caucasians. Network analysis identified differential lipid networks associated with risk of mortality. Our findings provide novel insight into the role of dyslipidemia in disease mortality and offer potential biomarkers for early prediction and risk reduction in American Indians and other ethnic groups.

Dyslipidemia has been associated with depression, but individual lipid species associated with depression remain largely unknown. The temporal relationship between lipid metabolism and the development of depression also remains to be determined. We studied 3721 fasting plasma samples from 1978 American Indians attending two exams (2001-2003, 2006-2009, mean ~5.5 years apart) in the Strong Heart Family Study. Plasma lipids were repeatedly measured by untargeted liquid chromatography-mass spectrometry (LC-MS). Depressive symptoms were assessed using the 20-item Center for Epidemiologic Studies for Depression (CES-D). Participants at risk for depression were defined as total CES-D score ≥16. Generalized estimating equation (GEE) was used to examine the associations of lipid species with incident or prevalent depression, adjusting for covariates. The associations between changes in lipids and changes in depressive symptoms were additionally adjusted for baseline lipids. We found that lower levels of sphingomyelins and glycerophospholipids and higher level of lysophospholipids were significantly associated with incident and/or prevalent depression. Changes in sphingomyelins, glycerophospholipids, acylcarnitines, fatty acids and triacylglycerols were associated with changes in depressive symptoms and other psychosomatic traits. We also identified differential lipid networks associated with risk of depression. The observed alterations in lipid metabolism may affect depression through increasing the activities of acid sphingomyelinase and phospholipase A2, disturbing neurotransmitters and membrane signaling, enhancing inflammation, oxidative stress, and lipid peroxidation, and/or affecting energy storage in lipid droplets or membrane formation. These findings illuminate the mechanisms through which dyslipidemia may contribute to depression and provide initial evidence for targeting lipid metabolism in developing preventive and therapeutic interventions for depression.

Telomeres shorten with age and shorter leukocyte telomere length (LTL) has been associated with various age-related diseases. Thus, LTL has been considered a biomarker of biological aging. Dyslipidemia is an established risk factor for most age-related metabolic disorders. However, little is known about the relationship between LTL and dyslipidemia. Lipidomics is a new biochemical technique that can simultaneously identify and quantify hundreds to thousands of small molecular lipid species. In a large population comprising 1843 well-characterized American Indians in the Strong Heart Family Study, we examined the lipidomic profile of biological aging assessed by LTL. Briefly, LTL was quantified by qPCR. Fasting plasma lipids were quantified by untargeted liquid chromatography-mass spectrometry. Lipids associated with LTL were identified by elastic net modeling. Of 1542 molecular lipids identified (518 known, 1024 unknown), 174 lipids (36 knowns) were significantly associated with LTL, independent of chronological age, sex, BMI, hypertension, diabetes status, smoking status, bulk HDL-C, and LDL-C. These findings suggest that altered lipid metabolism is associated with biological aging and provide novel insights that may enhance our understanding of the relationship between dyslipidemia, biological aging, and age-related diseases in American Indians.

Dyslipidemia associates with and usually precedes the onset of chronic kidney disease (CKD), but a comprehensive assessment of molecular lipid species associated with risk of CKD is lacking. Here, we sought to identify fasting plasma lipids associated with risk of CKD among American Indians in the Strong Heart Family Study, a large-scale community-dwelling of individuals, followed by replication in Mexican Americans from the San Antonio Family Heart Study and Caucasians from the Australian Diabetes, Obesity and Lifestyle Study. We also performed repeated measurement analysis to examine the temporal relationship between the change in the lipidome and change in kidney function between baseline and follow-up of about five years apart. Network analysis was conducted to identify differential lipid classes associated with risk of CKD. In the discovery cohort, we found that higher baseline level of multiple lipid species, including glycerophospholipids, glycerolipids and sphingolipids, was significantly associated with increased risk of CKD, independent of age, sex, body mass index, diabetes and hypertension. Many lipid species were replicated in at least one external cohort at the individual lipid species and/or the class level. Longitudinal change in the plasma lipidome was significantly associated with change in the estimated glomerular filtration rate after adjusting for covariates, baseline lipids and the baseline rate. Network analysis identified distinct lipidomic signatures differentiating high from low-risk groups. Thus, our results demonstrated that disturbed lipid metabolism precedes the onset of CKD. These findings shed light on the mechanisms linking dyslipidemia to CKD and provide potential novel biomarkers for identifying individuals with early impaired kidney function at preclinical stages.

BackgroundEpigenetic dysregulation has been proposed as a key mechanism for arsenic-related cardiovascular disease (CVD). We evaluated differentially methylated positions (DMPs) as potential mediators on the association between arsenic and CVD.MethodsBlood DNA methylation was measured in 2321 participants (mean age 56.2, 58.6% women) of the Strong Heart Study, a prospective cohort of American Indians. Urinary arsenic species were measured using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. We identified DMPs that are potential mediators between arsenic and CVD. In a cross-species analysis, we compared those DMPs with differential liver DNA methylation following early-life arsenic exposure in the apoE knockout (apoE-/-) mouse model of atherosclerosis.ResultsA total of 20 and 13 DMPs were potential mediators for CVD incidence and mortality, respectively, several of them annotated to genes related to diabetes. Eleven of these DMPs were similarly associated with incident CVD in 3 diverse prospective cohorts (Framingham Heart Study, Women's Health Initiative, and Multi-Ethnic Study of Atherosclerosis). In the mouse model, differentially methylated regions in 20 of those genes and DMPs in 10 genes were associated with arsenic.ConclusionsDifferential DNA methylation might be part of the biological link between arsenic and CVD. The gene functions suggest that diabetes might represent a relevant mechanism for arsenic-related cardiovascular risk in populations with a high burden of diabetes.

ObjectiveComprehensive assessment of alterations in lipid species preceding type 2 diabetes (T2D) is largely unknown. We aimed to identify plasma molecular lipids associated with risk of T2D in American Indians.Research design and methodsUsing untargeted liquid chromatography-mass spectrometry, we repeatedly measured 3,907 fasting plasma samples from 1,958 participants who attended two examinations (∼5.5 years apart) and were followed up to 16 years in the Strong Heart Family Study. Mixed-effects logistic regression was used to identify lipids associated with risk of T2D, adjusting for traditional risk factors. Repeated measurement analysis was performed to examine the association between change in lipidome and change in continuous measures of T2D, adjusting for baseline lipids. Multiple testing was controlled by false discovery rate at 0.05.ResultsHigher baseline level of 33 lipid species, including triacylglycerols, diacylglycerols, phosphoethanolamines, and phosphocholines, was significantly associated with increased risk of T2D (odds ratio [OR] per SD increase in log2-transformed baseline lipids 1.50-2.85) at 5-year follow-up. Of these, 21 lipids were also associated with risk of T2D at 16-year follow-up. Aberrant lipid profiles were also observed in prediabetes (OR per SD increase in log2-transformed baseline lipids 1.30-2.19 for risk lipids and 0.70-0.78 for protective lipids). Longitudinal changes in 568 lipids were significantly associated with changes in continuous measures of T2D. Multivariate analysis identified distinct lipidomic signatures differentiating high- from low-risk groups.ConclusionsLipid dysregulation occurs many years preceding T2D, and novel molecular lipids (both baseline level and longitudinal change over time) are significantly associated with risk of T2D beyond traditional risk factors. Our findings shed light on the mechanisms linking dyslipidemia to T2D and may yield novel therapeutic targets for early intervention tailored to American Indians.

Alzheimer's dementia (AD) begins many years before its clinical symptoms. Metabolic dysfunction represents a core feature of AD and cognitive impairment, but few metabolomic studies have focused on cognitive aging in midlife. Using an untargeted metabolomics approach, we identified metabolic predictors of cognitive aging in midlife using fasting plasma sample from 30 middle-aged (mean age 57.2), male-male twin pairs enrolled in the Vietnam Era Twin Study of Aging (VETSA). For all twin pairs, one twin developed incident MCI, whereas his co-twin brother remained to be cognitively normal during an average 5.5-year follow-up. Linear mixed model was used to identify metabolites predictive of MCI conversion or cognitive change over time, adjusting for traditional risk factors. Results from twins were replicated in an independent cohort of middle-aged adults (mean age 59.1) in the Wisconsin Registry for Alzheimer's Prevention (WRAP). Results in twins showed that higher baseline levels of four plasma metabolites, including sphingomyelin (d18:1/20:1 and d18:2/20:0), sphingomyelin (d18:1/22:1, d18:2/22:0, and d16:1/24:1), DAG (18:2/20:4), and hydroxy-CMPF, were significantly associated with a slower decrease in one or more domains of cognitive function. The association of sphingomyelin (d18:1/20:1 and d18:2/20:0) was replicated in WRAP. Our results support that metabolic perturbation occurs many years before cognitive impairment and plasma metabolites may serve as early biomarkers for prediction or monitoring of cognitive aging and AD in midlife.

Leukocyte telomere length (LTL) may be sensitive to psychosocial stressors such as discrimination. An inclusive examination of experiences of discrimination on LTL across racial/ethnic and sex groups is currently lacking. Baseline data were obtained from 369 White and African American patients with coronary artery disease (CAD) in the Mental Stress Ischemia Mechanisms and Prognosis Study. LTL was measured from peripheral blood leukocytes by quantitative polymerase chain reaction and calculated in kilobase pairs. Discrimination was measured using the 10-item Everyday Discrimination Scale (EDS). Responses were rated using 4-point Likert scales ranging from never = 1 to often = 4 and summed. Regression models were stratified by race/ethnicity and sex to estimate associations between discrimination and LTL. Each 10-unit increase in experiences of everyday discrimination was associated with an average of .20 fewer kilobase pairs (or 200 base pairs) among both African American women (β = -0.19; 95% CI: -0.35, -0.04; p-value: 0.02) and White women (β = -0.19; 95% CI: -0.37, -0.01; p-value: 0.04), after adjusting for basic demographic factors. Results were similar after further adjusting for behavioral, disease, and psychosocial risk factors (depression and stress). There were no significant associations between experiences of everyday discrimination and LTL for White men or African American men. Overall, experiences of discrimination were associated with shorter LTL among women and not in men. Discrimination may be a potential source of stress associated with shorter LTL among women with CAD. Future studies should explore longitudinal associations between everyday experiences of discrimination and telomere length and also with adverse cardiovascular outcomes.

Objective: Although fMRI has been widely used in the field of acupuncture. However, the literature analysis in this field still has significant differences. This study summarizes the current status of functional magnetic resonance imaging (fMRI) in the field of acupuncture and moxibustion and predicts its future trends through Web of Science bibliometric analysis. Methods: This study uses "fMRI" and "acupuncture" as keywords to search for literature related to functional magnetic resonance imaging (fMRI) in acupuncture research in the Web of Science Core Collection database from January 1, 2004, to April 30, 2024. Visualization analyses were conducted using Citespace (version 6.3 R1) and VOSviewer (version 1.6.20). Citespace was employed to analyze annual publications, countries, institutions, keywords, and co-cited references. VOSviewer was used to analyze authors and co-cited authors, as well as journals and co-cited journals. Results: From 2004 to 2024, a total of 967 publications were retrieved, of which 557 were included after screening. Despite annual fluctuations, the overall trend shows an increase. China and the Chinese Academy of Sciences are the countries and institutions with the highest number of publications, with Tian, J being the author with the most publications, and Kong, J having the highest Co-citation frequency. The article by Dhond, RP, published in 2008, has the highest Co-citation frequency among the co-cited literature. Evidence-based Complementary and Alternative Medicine is the journal with the most publications, while Neuroimage is the co-cited journal with the highest citation frequency. Keyword co-occurrence and burst reveal the main research hotspots, including the diversity of intervention methods, cortical activation, mechanisms related to pain-associated diseases, and brain-related diseases. Keyword burst detection reflects emerging trends, including meta-analysis and systematic reviews, the relationship between ischemic stroke and women, and the connection between mild cognitive impairment and prevention. Conclusion: This study employs bibliometric methods to explore the current status, research hotspots, and frontier issues regarding the application of functional magnetic resonance imaging (fMRI) technology in the field of acupuncture, providing new perspectives and directions for acupuncture fMRI research. [ABSTRACT FROM AUTHOR]

BackgroundGenome-wide single marker and gene-based meta-analyses of long-term average (LTA) blood pressure (BP) phenotypes may reveal novel findings for BP.Methods and resultsWe conducted genome-wide analysis among 18 422 East Asian participants (stage 1) followed by replication study of ≤46 629 participants of European ancestry (stage 2). Significant single-nucleotide polymorphisms and genes were determined by a P

RationaleLeukocyte telomere length (LTL) is a biological marker of aging, and shorter LTL is associated with adverse cardiovascular outcomes. Reduced regenerative capacity has been proposed as a mechanism. Bone marrow-derived circulating progenitor cells are involved in tissue repair and regeneration.ObjectiveMain objective of this study was to examine the relationship between LTL and progenitor cells and their impact on adverse cardiovascular outcomes.Methods and resultsWe measured LTL by quantitative polymerase chain reaction in 566 outpatients (age: 63±9 years; 76% men) with coronary artery disease. Circulating progenitor cells were enumerated by flow cytometry. After adjustment for age, sex, race, body mass index, smoking status, and previous myocardial infarction, a shorter LTL was associated with a lower CD34+ cell count: for each 10% shorter LTL, CD34+ levels were 5.2% lower (P

Motivation 5-Hydroxymethylcytosine (5hmC), a crucial epigenetic mark with a significant role in regulating tissue-specific gene expression, is essential for understanding the dynamic functions of the human genome. Despite its importance, predicting 5hmC modification across the genome remains a challenging task, especially when considering the complex interplay between DNA sequences and various epigenetic factors such as histone modifications and chromatin accessibility. Results Using tissue-specific 5hmC sequencing data, we introduce Deep5hmC, a multimodal deep learning framework that integrates both the DNA sequence and epigenetic features such as histone modification and chromatin accessibility to predict genome-wide 5hmC modification. The multimodal design of Deep5hmC demonstrates remarkable improvement in predicting both qualitative and quantitative 5hmC modification compared to unimodal versions of Deep5hmC and state-of-the-art machine learning methods. This improvement is demonstrated through benchmarking on a comprehensive set of 5hmC sequencing data collected at four developmental stages during forebrain organoid development and across 17 human tissues. Compared to DeepSEA and random forest, Deep5hmC achieves close to 4% and 17% improvement of Area Under the Receiver Operating Characteristic (AUROC) across four forebrain developmental stages, and 6% and 27% across 17 human tissues for predicting binary 5hmC modification sites; and 8% and 22% improvement of Spearman correlation coefficient across four forebrain developmental stages, and 17% and 30% across 17 human tissues for predicting continuous 5hmC modification. Notably, Deep5hmC showcases its practical utility by accurately predicting gene expression and identifying differentially hydroxymethylated regions (DhMRs) in a case–control study of Alzheimer's disease (AD). Deep5hmC significantly improves our understanding of tissue-specific gene regulation and facilitates the development of new biomarkers for complex diseases. Availability and implementation Deep5hmC is available via https://github.com/lichen-lab/Deep5hmC [ABSTRACT FROM AUTHOR]

Telomere length, a marker of biological aging, has been associated with cardiovascular disease (CVD) and its risk factors. Ideal cardiovascular health (CVH), defined by the American Heart Association (AHA), has also been associated with a reduced risk of CVD, but the relationship between telomere length and ideal CVH is unclear. We measured leukocyte telomere length (LTL) by qPCR in 2568 American Indians in the Strong Heart Family Study (SHFS). All participants were free of overt CVD at enrollment (2001-2003). CVH indices included four behavioral factors (smoking, physical activity, diet, BMI) and three health factors (blood pressure, cholesterol, fasting glucose). Each index was categorized as poor, intermediate, or ideal according to the AHAs guideline. CVH was further categorized into below average (0-1), average (2-3) and above average (≥4) based on the total number of ideal indices. Results showed that, 29, 50 and 21 % of study participants had below average, average, and above average CVH, respectively. Participants with above average CVH had significantly longer LTL than those with below average CVH (β = 0.034, P = 0.042) after adjusting for age, sex, education level, marital status, processed meat consumption, alcohol consumption, and study site. Compared to the U.S. general population, American Indians achieved lower rates for five out of the seven ideal CVH metrics, including smoking, BMI, physical activity, diet, and blood pressure. Achieving four or more ideal CVH metrics was significantly associated with longer LTL. This finding suggests that achieving an ideal CVH may prevent or delay CVD, probably through promoting healthy aging.

Patients with depression have an increased risk for many aging-related disorders, but the biological mechanisms underlying this link remain to be determined. Here we examined the association between depressive symptoms and leukocyte telomere length (LTL), a marker of biological aging, among 2,175 American Indians participating in the Strong Heart Family Study. Depressive symptoms were assessed by the Center for Epidemiologic Studies of Depression Scale (CES-D), which was categorized into four levels: none (< 10), mild (10-15), moderate (16 -24), and severe (> 24). LTL (T/S ratio) was quantified by qPCR. The association between depressive symptoms and LTL was examined by multivariate generalized estimating equation models, adjusting for sociodemographic factors, lifestyle factors, and chronic conditions. Results showed that individuals with a higher level of depressive symptoms had shorter LTL. Specifically, LTL in participants reporting none, mild, moderate, and severe depressive symptoms were 1.000, 0.999, 0.988, and 0.966, respectively (P for trend = 0.0278). Moreover, gender appears to modulate the effect of reported depressive symptoms that fall in the severe range (CES-D > 24) on LTL (P for interaction = 0.0346). Our results suggest that depressive symptoms may accelerate biological aging through pathways beyond traditional risk factors in American Indians.

Telomere length, a marker of biological aging, has been associated with cardiovascular disease (CVD). Increased arterial stiffness, an indicator of arterial aging, predicts adverse CVD outcomes. However, the relationship between telomere length and arterial stiffness is less well studied. Here we examined the cross-sectional association between leukocyte telomere length (LTL) and arterial stiffness in 2,165 American Indians in the Strong Heart Family Study (SHFS). LTL was measured by qPCR. Arterial stiffness was assessed by stiffness index β. The association between LTL and arterial stiffness was assessed by generalized estimating equation model, adjusting for sociodemographics (age, sex, education level), study site, metabolic factors (fasting glucose, lipids, systolic blood pressure, and kidney function), lifestyle (BMI, smoking, drinking, and physical activity), and prevalent CVD. Results showed that longer LTL was significantly associated with a decreased arterial stiffness (β=-0.070, P=0.007). This association did not attenuate after further adjustment for hsCRP (β=-0.071, P=0.005) or excluding participants with overt CVD (β=-0.068, P=0.012), diabetes (β=-0.070, P=0.005), or chronic kidney disease (β=-0.090, P=0.001). In summary, shorter LTL was significantly associated with an increased arterial stiffness, independent of known risk factors. This finding may shed light on the potential role of biological aging in arterial aging in American Indians.