Association of bone fracture with 30-year body mass index (BMI) trajectories: findings from the Framingham Heart Study : Bone fracture and 30-year BMI trajectories.

A knowledge gap exists in associating later life's osteoporotic fracture and middle adulthood's BMI trajectories. We observed an association showing those transitioning from overweight to normal weight face a higher fracture risk in late adulthood, emphasizing the potential benefits of maintaining a stable BMI to reduce late-life fractures. PURPOSE: Numerous studies on the relationship between obesity and fractures have relied on body mass index (BMI) at a single time point, yielding inconclusive results. This study investigated the association of BMI trajectories over middle adulthood with fracture risk in late adulthood. METHODS: This prospective cohort study analyzed 1772 qualified participants from the Framingham Original Cohort Study, with 292 (16.5%) incident fractures during an average of 17.1-year follow-up. We constructed BMI trajectories of age 35-64 years based on latent class mixed modeling and explored their association with the risk of fracture after 65 years using the Cox regression. RESULTS: The result showed that compared to the BMI trajectory Group 4 (normal to slightly overweight; see "Methods" for detailed description), Group 1 (overweight declined to normal weight) had a higher all-fracture risk after age 65 (hazard ratio [HR], 2.22, 95% CI, 1.13-4.39). The secondary analysis focusing on lower extremity fractures (pelvis, hip, leg, and foot) showed a similar association pattern. CONCLUSIONS: This study suggested that people whose BMI slightly increased from normal weight to low-level overweight during 30 years of middle adulthood confer a significantly lower risk of fracture in later life than those whose BMI declined from overweight to normal weight. This result implies the potentially beneficial effects of avoiding weight loss to normal weight during middle adulthood for overweight persons, with reduced fracture risk in late life.

Patterns of Aging Changes in Bodyweight May Predict Alzheimer's Disease.

Relationships between patterns of aging-changes in bodyweight and AD are not fully understood. We compared mean age-trajectories of weight between those who did and did not develop late-onset-AD, and evaluated impact of age at maximum weight (AgeMax), and slope of decline in weight, on AD risk. Women with late-onset-AD had lower weight three or more decades before AD onset, and ∼10 years younger AgeMax, compared to AD-free women. APOE4 carriers had younger AgeMax and steeper slope. Older AgeMax and flatter slope predicted lower AD risk. Premature decline in weight could be a sign of accelerated physical aging contributing to AD.

AORTA Gene: Polygenic prediction improves detection of thoracic aortic aneurysm.

Background: Thoracic aortic disease is an important cause of morbidity and mortality in the US, and aortic diameter is a heritable contributor to risk. Could a polygenic prediction of ascending aortic diameter improve detection of aortic aneurysm? Methods: Deep learning was used to measure ascending thoracic aortic diameter in 49,939 UK Biobank participants. A genome-wide association study (GWAS) was conducted in 39,524 participants and leveraged to build a 1.1 million-variant polygenic score with PRScs-auto. Aortic diameter prediction models were built with the polygenic score ("AORTA Gene") and without it. The models were tested in a held-out set of 4,962 UK Biobank participants and externally validated in 5,469 participants from Mass General Brigham Biobank (MGB), 1,298 from the Framingham Heart Study (FHS), and 610 participants from All of Us. Results: In each test set, the AORTA Gene model explained more of the variance in thoracic aortic diameter compared to clinical factors alone: 39.9% (95% CI 37.8-42.0%) vs 29.2% (95% CI 27.1-31.4%) in UK Biobank, 36.5% (95% CI 34.4-38.5%) vs 32.5% (95% CI 30.4-34.5%) in MGB, 41.8% (95% CI 37.7-45.9%) vs 33.0% (95% CI 28.9-37.2%) in FHS, and 34.9% (95% CI 28.8-41.0%) vs 28.9% (95% CI 22.9-35.0%) in All of Us. AORTA Gene had a greater AUROC for identifying diameter ≥4cm in each test set: 0.834 vs 0.765 (P=7.3E-10) in UK Biobank, 0.808 vs 0.767 in MGB (P=4.5E-12), 0.856 vs 0.818 in FHS (P=8.5E-05), and 0.827 vs 0.791 (P=7.8E-03) in All of Us. Conclusions: Genetic information improved estimation of thoracic aortic diameter when added to clinical risk factors. Larger and more diverse cohorts will be needed to develop more powerful and equitable scores.

Smoking, blood DNA methylation sites and lung cancer risk.

Altered DNA methylation (DNAm) might be a biological intermediary in the pathway from smoking to lung cancer. In this study, we investigated the contribution of differential blood DNAm to explain the association between smoking and lung cancer incidence. Blood DNAm was measured in 2321 Strong Heart Study (SHS) participants. Incident lung cancer was assessed as time to event diagnoses. We conducted mediation analysis, including validation with DNAm and paired gene expression data from the Framingham Heart Study (FHS). In the SHS, current versus never smoking and pack-years single-mediator models showed, respectively, 29 and 21 differentially methylated positions (DMPs) for lung cancer with statistically significant mediated effects (14 of 20 available, and five of 14 available, positions, replicated, respectively, in FHS). In FHS, replicated DMPs showed gene expression downregulation largely in trans, and were related to biological pathways in cancer. The multimediator model identified that DMPs annotated to the genes AHRR and IER3 jointly explained a substantial proportion of lung cancer. Thus, the association of smoking with lung cancer was partly explained by differences in baseline blood DNAm at few relevant sites. Experimental studies are needed to confirm the biological role of identified eQTMs and to evaluate potential implications for early detection and control of lung cancer.

Association of Depressive Symptom Trajectory With Physical Activity Collected by mHealth Devices in the Electronic Framingham Heart Study: Cohort Study.

BACKGROUND: Few studies have examined the association between depressive symptom trajectories and physical activity collected by mobile health (mHealth) devices. OBJECTIVE: We aimed to investigate if antecedent depressive symptom trajectories predict subsequent physical activity among participants in the electronic Framingham Heart Study (eFHS). METHODS: We performed group-based multi-trajectory modeling to construct depressive symptom trajectory groups using both depressive symptoms (Center for Epidemiological Studies-Depression [CES-D] scores) and antidepressant medication use in eFHS participants who attended 3 Framingham Heart Study research exams over 14 years. At the third exam, eFHS participants were instructed to use a smartphone app for submitting physical activity index (PAI) surveys. In addition, they were provided with a study smartwatch to track their daily step counts. We performed linear mixed models to examine the association between depressive symptom trajectories and physical activity including app-based PAI and smartwatch-collected step counts over a 1-year follow-up adjusting for age, sex, wear hour, BMI, smoking status, and other health variables. RESULTS: We identified 3 depressive symptom trajectory groups from 722 eFHS participants (mean age 53, SD 8.5 years; n=432, 60% women). The low symptom group (n=570; mean follow-up 287, SD 109 days) consisted of participants with consistently low CES-D scores, and a small proportion reported antidepressant use. The moderate symptom group (n=71; mean follow-up 280, SD 118 days) included participants with intermediate CES-D scores, who showed the highest and increasing likelihood of reporting antidepressant use across 3 exams. The high symptom group (n=81; mean follow-up 252, SD 116 days) comprised participants with the highest CES-D scores, and the proportion of antidepressant use fell between the other 2 groups. Compared to the low symptom group, the high symptom group had decreased PAI (mean difference -1.09, 95% CI -2.16 to -0.01) and the moderate symptom group walked fewer daily steps (823 fewer, 95% CI -1421 to -226) during the 1-year follow-up. CONCLUSIONS: Antecedent depressive symptoms or antidepressant medication use was associated with lower subsequent physical activity collected by mHealth devices in eFHS. Future investigation of interventions to improve mood including via mHealth technologies to help promote people's daily physical activity is needed.

Association of healthy dietary patterns and cardiorespiratory fitness in the community.

AIMS: To evaluate the associations of dietary indices and quantitative cardiorespiratory fitness (CRF) measures in a large, community-based sample harnessing metabolomic profiling to interrogate shared biology. METHODS AND RESULTS: Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise tests for CRF quantification (via peak VO2) and completed semi-quantitative food frequency questionnaires. Dietary quality was assessed by the Alternative Healthy Eating Index (AHEI) and Mediterranean-style Diet Score (MDS), and fasting blood concentrations of 201 metabolites were quantified. In 2380 FHS participants (54 ± 9 years, 54% female, body mass index 28 ± 5 kg/m2), 1 SD higher AHEI and MDS were associated with 5.2% (1.2 mL/kg/min, 95% CI 4.3-6.0%, P < 0.0001) and 4.5% (1.0 mL/kg/min, 95% CI 3.6-5.3%, P < 0.0001) greater peak VO2 in linear models adjusted for age, sex, total daily energy intake, cardiovascular risk factors, and physical activity. In participants with metabolite profiling (N = 1154), 24 metabolites were concordantly associated with both dietary indices and peak VO2 in multivariable-adjusted linear models (FDR < 5%). Metabolites that were associated with lower CRF and poorer dietary quality included C6 and C7 carnitines, C16:0 ceramide, and dimethylguanidino valeric acid, and metabolites that were positively associated with higher CRF and favourable dietary quality included C38:7 phosphatidylcholine plasmalogen and C38:7 and C40:7 phosphatidylethanolamine plasmalogens. CONCLUSION: Higher diet quality is associated with greater CRF cross-sectionally in a middle-aged community-dwelling sample, and metabolites highlight potential shared favourable effects on cardiometabolic health.

This study seeks to address whether healthy dietary patterns relate to gold-standard measures of physical fitness in community-dwelling adults and how circulating metabolites can demonstrate biological relationships between diet and fitness. Healthy diet is associated with greater physical fitness in middle-aged adults. The beneficial relationship between diet and fitness may be partly explained by favourable metabolic health.

A Healthy Diet is Associated with a Lower Risk of Hepatic Fibrosis.

BACKGROUND: Higher diet quality is associated with a lower risk of NAFLD. OBJECTIVES: We examined the relationship between diet quality and hepatic fibrosis. METHODS: We analyzed cross-sectional associations between 3 a priori diet quality scores-the Dietary Approaches to Stop Hypertension (DASH) score, the Alternative Healthy Eating Index (AHEI), and a modified Mediterranean-style Diet Score (MDS)-and hepatic fat [controlled attenuation parameter (CAP)] and fibrosis [liver stiffness measurement (LSM)] measured by vibration-controlled transient elastography (VCTE) in 2532 Framingham Heart Study (FHS) participants and 3295 participants of the National Health and Nutrition Examination Survey (NHANES). RESULTS: Higher diet quality scores were associated with lower LSM in both FHS and NHANES after adjustment for demographic and lifestyle factors. Additional adjustment for CAP or BMI attenuated the observed associations. Association strength was similar across all 3 diet quality scores. Fixed-effect meta-analysis demonstrated that, under CAP-adjusted models, the LSM decreases associated with 1-SD increase of the DASH, AHEI, and MDS scores were 2% (95% CI: 0.7%, 3.3%; P = 0.002), 2% (95% CI: 0.7%, 3.3%; P = 0.003), and 1.7% (95% CI: 0.7%, 2.6%; P = 0.001), respectively, whereas in the meta-analysis of BMI-adjusted models, LSM reductions associated with 1-SD increase of the DASH, AHEI, and MDS scores were 2.2% (95% CI: -0.1%, 2.2%; P = 0.07), 1.5% (95% CI: 0.3%, 2.7%; P = 0.02), and 0.9 (95% CI: -0.1%, 1.9%; P = 0.07), respectively. CONCLUSIONS: We demonstrated associations of higher diet quality with favorable hepatic fat and fibrosis measures. Our data suggest that a healthy diet may reduce the likelihood of obesity and hepatic steatosis as well as the progression of steatosis to fibrosis.

Plasma Protein Biomarkers of Healthy Dietary Patterns: Results from the Atherosclerosis Risk in Communities Study and the Framingham Heart Study.

BACKGROUND: Molecular mechanisms underlying the benefits of healthy dietary patterns are poorly understood. Identifying protein biomarkers of dietary patterns can contribute to characterizing biological pathways influenced by food intake. OBJECTIVES: This study aimed to identify protein biomarkers associated with four indexes of healthy dietary patterns: Healthy Eating Index-2015 (HEI-2015); Alternative Healthy Eating Index-2010 (AHEI-2010); DASH diet; and alternate Mediterranean Diet (aMED). METHODS: Analyses were conducted on 10,490 Black and White men and women aged 49-73 y from the ARIC study at visit 3 (1993-1995). Dietary intake data were collected using a food frequency questionnaire, and plasma proteins were quantified using an aptamer-based proteomics assay. Multivariable linear regression models were used to examine the association between 4955 proteins and dietary patterns. We performed pathway overrepresentation analysis for diet-related proteins. An independent study population from the Framingham Heart Study was used for replication analyses. RESULTS: In the multivariable-adjusted models, 282 out of 4955 proteins (5.7%) were significantly associated with at least one dietary pattern (HEI-2015: 137; AHEI-2010: 72; DASH: 254; aMED: 35; P value < 0.05/4955 = 1.01 × 10-5). There were 148 proteins that were associated with only one dietary pattern (HEI-2015: 22; AHEI-2010: 5; DASH: 121; aMED: 0), and 20 proteins were associated with all four dietary patterns. Five unique biological pathways were significantly enriched by diet-related proteins. Seven out of 20 proteins associated with all dietary patterns in the ARIC study were available for replication analyses, and 6 out of these 7 proteins were consistent in direction and significantly associated with at least 1 dietary pattern in the Framingham Heart Study (HEI-2015: 2; AHEI-2010: 4; DASH: 6; aMED: 4; P value < 0.05/7 = 7.14 × 10-3). CONCLUSIONS: A large-scale proteomic analysis identified plasma protein biomarkers that are representative of healthy dietary patterns among middle-aged and older US adult population. These protein biomarkers may be useful objective indicators of healthy dietary patterns.

Examination of potentially modifiable dementia risk factors across the adult life course: The Framingham Heart Study.

INTRODUCTION: We examined for associations between potentially modifiable risk factors across the adult life course and incident dementia. METHODS: Participants from the Framingham Heart Study were included (n = 4015). Potential modifiable risk factors included education, alcohol intake, smoking, body mass index (BMI), physical activity, social network, diabetes, and hypertension. Cox models were used to examine associations between each factor and incident dementia, stratified by early adult life (33-44 years), midlife (45-65 years), and late life (66-80 years). RESULTS: Increased dementia risk was associated with diabetes (hazard ratio [HR] = 1.62; 95% confidence interval [CI] = 1.07-2.46) and physical inactivity (HR = 1.57; 95% CI = 1.12-2.20) in midlife, and with obesity (HR = 1.76; 95% CI = 1.08-2.87) in late life. Having multiple potential modifiable risk factors in midlife and late life was associated with greater risk. DISCUSSION: Potentially modifiable risk factors individually have limited impact on dementia risk in this population across the adult life course, although in combination they may have a synergistic effect. HIGHLIGHTS: Diabetes and physical inactivity in midlife is associated with increased dementia risk. Obesity in late life is associated with increased dementia risk. Having more potentially modifiable risk factors in midlife and late life is associated with greater dementia risk.

High consumption of whole grain foods decreases the risk of dementia and Alzheimer's disease: Framingham Offspring Cohort.

AIMS: To examine the longitudinal associations between total and individual whole grain (WG) food intake and the risk of all-cause dementia and Alzheimer's disease (AD) dementia. METHODS: This study included 2958 subjects (mean age at baseline was 61 ± 9 years) from the Framingham Offspring Cohort. Standardized interviews, physician examinations, and laboratory tests were collected approximately every 4 years, and the Food Frequency Questionnaire (FFQ) was conducted in cycle 5. Proportional hazards models and cubic spline regression examined associations between WG foods and all-cause dementia and AD dementia. RESULTS: Over an average of 12.6 years of follow-up, there were 322 dementia cases, of which 247 were AD dementia. After multivariate and dietary adjustments, individuals with the highest category for total WG food consumption had a lower risk of all-cause dementia [HR 0.66, 95% confidence interval (CI) 0.51-0.81] and AD dementia (HR 0.60, 95% CI 0.46-0.78) than individuals with the lowest category. The results remained comparable in different subgroups stratifying for age, sex, education, body mass index, and smoking status without significant interaction. Moreover, these inverse associations were seen for most individual WG foods except popcorn. A nonlinear dose-response association was shown between total WG intake and all-cause dementia and AD dementia, where the rate reduction slightly plateaued at more than one and two servings/day, respectively. CONCLUSIONS: Higher consumption of total and several common individual WG foods was strongly associated with a lower risk of all-cause dementia and AD dementia.

Higher Dietary Inflammatory Index scores are associated with brain MRI markers of brain aging: Results from the Framingham Heart Study Offspring cohort.

INTRODUCTION: We investigated cross-sectional associations between the Dietary Inflammatory Index (DII) and measures of brain volume and cerebral small vessel disease among participants of the Framingham Heart Study Offspring cohort. METHODS: A total of 1897 participants (mean ± standard deviation, age 62±9) completed Food Frequency Questionnaires and brain magnetic resonance imaging (MRI). RESULTS: Higher (pro-inflammatory) DII scores, averaged across a maximum of three time points, were associated with smaller total brain volume (beta ± standard error: -0.16 ± 0.03; P < .0001) after adjustment for demographic, clinical, and lifestyle covariates. In addition, higher DII scores were associated with smaller total gray matter volume (-0.08 ± 0.03; P = .003) and larger lateral ventricular volume (0.04 ± 0.02; P = .03). No associations were observed with other brain MRI measures. DISCUSSION: Our findings showed associations between higher DII scores and global brain MRI measures. As we are one of the first groups to report on the associations between higher DII scores and brain volume, replication is needed to confirm our findings.

Trajetórias e determinantes do alto risco cardiovascular de 30 anos entre participantes de uma coorte brasileira (Estudo CUME) / Trajectories and determinants of 30-year high cardiovascular risk among participants in a Brazilian cohort (CUME Study)

Introdução: As doenças cardiovasculares são o principal problema de saúde pública em todo o mundo. Portanto, a avaliação do risco cardiovascular, com a identificação de seus fatores de risco e de proteção e de suas trajetórias ao longo do tempo são importantes para a proposição, a consolidação e a implementação de medidas de prevenção da ocorrência de doenças cardiovasculares. Objetivo geral: Analisar a trajetória e os determinantes do alto risco cardiovascular de 30 anos em participantes da Coorte de Universidades Mineiras (Estudo CUME). Métodos: Inicialmente, foi realizada uma revisão integrativa da literatura e, em seguida, dois estudos de coorte prospectiva. A) Artigo 1 ­ revisão integrativa da literatura sobre a estimação do alto risco cardiovascular e seus fatores associados, realizada nas bases Medical Literature Analysis and Retrievel System Online, Web of Science, Excerpta Medica Database, Cumulative Index to Nursing and Allied Health Literature e no portal Biblioteca Virtual de Saúde; B) Artigo 2 ­ Coorte aberta prospectiva desenvolvida com 2.854 participantes do Estudo CUME, que é uma pesquisa multicêntrica conduzida com egressos de sete instituições públicas federais de ensino superior do Estado de Minas Gerais desde 2016. A incidência do alto risco cardiovascular de 30 anos foi calculada usando o escore de Framingham e seus determinantes foram estimados usando análise multivariada hierárquica pela técnica de regressão de Cox; C) Artigo 3 ­ Estudo prospectivo fechado desenvolvido com 1.286 participantes da CUME, que responderam ao questionário da linha de base em 2016, aos questionários de seguimento de dois anos (2018) e de quatro anos (2020). O risco cardiovascular foi avaliado com o escore de Framingham de 30 anos. A identificação das trajetórias do risco cardiovascular foi realizada com a técnica de modelagem de crescimento de classe latente com o uso do modelo normal censurado. A análise dos fatores independentemente associados a cada uma das trajetórias foi conduzida com a técnica de regressão logística multinominal. Resultados: Artigo 1 ­ foram selecionados 13 artigos com um ou mais fatores associados ao alto risco cardiovascular, segundo o escore de Framingham de 10 anos. Nenhum artigo investigou os fatores associados ao alto risco cardiovascular de 30 anos. Artigo 2 ­ após média de 2,62 anos de seguimento, a incidência do alto risco cardiovascular de 30 anos foi 8,1 casos/1.000 pessoas-ano no sexo feminino e 20,2 casos/1.000 pessoas-ano no sexo masculino. Sexo masculino (Hazard Ratio ­ HR: 2,34; IC 95%: 1,58 - 3,46), trabalhar (HR: 2,13; IC 95%: 1,13 - 3,99), alto consumo de alimentos processados (HR: 2,44; 95% CI: 1,21 - 4,90) e ser ativo fisicamente (HR: 0,63; IC 95%: 0,41 - 0,98) se associaram independentemente ao alto risco cardiovascular de 30 anos; Artigo 3 - Três trajetórias de risco cardiovascular de 30 anos foram identificadas: Baixo-Baixo (68,3%), Médio-Médio (26,2%) e Alto-Alto (5,5%). Ao longo do tempo, o risco cardiovascular apresentou discreto aumento para a trajetória Baixo-Baixo (2,9%), moderado aumento para a trajetória Médio-Médio (7,6%) e elevado aumento para a trajetória Alto-Alto (13%). O sexo masculino, viver em união estável, ter consumos moderado e alto de alimentos ultraprocessados se associaram positivamente às trajetórias de risco cardiovascular Médio-Médio e Alto-Alto. Ainda, ter formação profissional fora da área da saúde e estar trabalhando se associaram positivamente à trajetória de risco cardiovascular Médio-Médio, enquanto ser ativo fisicamente se associou negativamente à trajetória de risco cardiovascular Alto-Alto. Conclusão: Poucos estudos foram conduzidos para avaliar o alto risco cardiovascular de 30 anos, sendo que em nenhum deles foram estimados fatores associados ao desfecho. Nossos achados científicos indicaram que praticar atividade física reduz a incidência do alto risco cardiovascular de 30 anos. Homens, pessoas que trabalham e com consumo elevado de alimentos processados devem ser monitorados com maior cautela, pois apresentaram maior susceptibilidade de ocorrência do alto risco cardiovascular de 30 anos. Adultos jovens e com melhor situação socioeconômica possuem uma trajetória de baixo risco cardiovascular de 30 anos, entretanto, há uma tendência de piora desta trajetória ao longo do tempo devido aos maus hábitos de vida. Dessa forma, é essencial a implementação de estratégias de prevenção para evitar o adoecimento cardiovascular.

Introduction: Cardiovascular diseases are the main public health problem worldwide. Therefore, the assessment of cardiovascular risk, with the identification of its risk and protection factors and their trajectories over time, are important for proposing, consolidating and implementing measures to prevent the occurrence of cardiovascular diseases. General objective: To analyze the 30-year trajectory and determinants of high cardiovascular risk in participants of the Cohort of Universities of Minas Gerais (CUME Study). Methods: Initially, an integrative literature review was performed, followed by two prospective cohort studies. A) Article 1 ­ integrative review of the literature on the estimation of high cardiovascular risk and its associated factors, carried out in the databases Medical Literature Analysis and Retrievel System Online, Web of Science, Excerpta Medica Database, Cumulative Index to Nursing and Allied Health Literature and the Virtual Health Library portal; B) Article 2 ­ Prospective open cohort developed with 2,854 participants of the CUME Study, which is a multicenter research conducted with graduates from seven federal public institutions of higher education in the State of Minas Gerais since 2016. The incidence of high cardiovascular risk at 30 years was calculated using the Framingham score and its determinants were estimated using hierarchical multivariate analysis by the Cox regression technique; C) Article 3 ­ Prospective closed study developed with 1,286 participants from CUME, who answered the baseline questionnaire in 2016, the two-year follow-up questionnaire in 2018 and the four-year follow-up questionnaire in 2020. The risk Cardiovascular was assessed using the 30-year Framingham score. The identification of cardiovascular risk trajectories was performed using the latent class growth modeling technique using the normal censored model. The analysis of the factors independently associated with each of the trajectories was conducted using the multinomial logistic regression technique. Results: Article 1 ­ 13 articles were selected with one or more factors associated with high cardiovascular risk, according to the Framingham score over 10 years. No article investigated the factors associated with 30-year high cardiovascular risk. Article 2 ­ After an average of 2.62 years of follow-up, the incidence of high cardiovascular risk at 30 years was 8.1 cases/1,000 person-years in females and 20.2 cases/1,000 person-years in males. Male sex (Hazard Ratio ­ HR: 2.34; 95% CI: 1.58 - 3.46), work (HR: 2.13; 95% CI: 1.13 - 3.99), high food intake processed foods (HR: 2.44; 95% CI: 1.21 - 4.90) and being physically active (HR: 0.63; 95% CI: 0.41 - 0.98) were independently associated with high cardiovascular risk 30 years old; Article 3 - Three 30-year cardiovascular risk trajectories were identified: Low-Low (68.3%), Medium-Medium (26.2%) and High-High (5.5%). Over time, cardiovascular risk showed a slight increase for the Low-Low trajectory (2.9%), a moderate increase for the Medium-Medium trajectory (7.6%) and a high increase for the High-High trajectory (13%). Being male, living in a stable relationship, having moderate and high consumption of ultra-processed foods were positively associated with Medium-Medium and High-High cardiovascular risk trajectories. Also, having professional training outside the health area and being working were positively associated with the Medium-Medium cardiovascular risk trajectory, while being physically active was negatively associated with the High-High cardiovascular risk trajectory. Conclusion: Few studies were conducted to assess the 30-year high cardiovascular risk, and none of them estimated factors associated with the outcome. Our scientific findings indicated that practicing physical activity reduces the incidence of 30-year high cardiovascular risk. Men, people who work and with a high consumption of processed foods should be monitored with greater caution, as they were more susceptible to the occurrence of the high cardiovascular risk of 30 years. Young adults with better socioeconomic status have a 30-year trajectory of low cardiovascular risk, however, there is a tendency for this trajectory to worsen over time due to bad lifestyle habits. Thus, it is essential to implement prevention strategies to avoid cardiovascular disease.

The 30-year cardiovascular risk trajectories and their independently associated factors in participants of a Brazilian cohort (CUME Study) / As trajetórias de risco cardiovascular de 30 anos e seus fatores independentemente associados em participantes de uma coorte brasileira (Estudo CUME) / Las trayectorias de riesgo cardiovascular de 30 años y sus factores asociados de forma independiente en participantes de una cohorte brasileña (Estudio CUME)

Abstract: We aimed to analyze the different trajectories of 30-year cardiovascular risk (CVR) and its independently associated factors in participants of the CUME Study, a prospective study with alumni from federal universities of Minas Gerais State, Brazil. In this study, 1,286 participants who answered the baseline (2016) and follow-up (2018 and 2020) questionnaires were included. Trajectories of CVR, according to the Framingham score, were identified with the latent class growth modelling technique with the use of the censored normal model. Analysis of the factors independently associated with each of the trajectories was conducted with multinomial logistic regression technique. Three CVR trajectories were identified: Low-Low (68.3%), Medium-Medium (26.2%), and High-High (5.5%). Male sex, living in a stable union, and having moderate and high intakes of ultra-processed foods were positively associated with the Medium-Medium and High-High CVR trajectories. Having non-healthcare professional training and working were positively associated with the Medium-Medium CVR trajectory, whereas being physically active was negatively associated with the High-High CVR trajectory. In conclusion, more than one-third of participants had CVR trajectories in the Medium-Medium and High-High categories. Food consumption and physical activity are modifiable factors that were associated with these trajectories; thus, implementing health promotion measures could help prevent the persistence or worsen of CVR. On the other hand, sociodemographic and labor characteristics are non-modifiable factors that were associated with Medium-Medium and High-High trajectories, which could help identify people who should be monitored with more caution by health services.

Resumo: Nosso objetivo foi analisar as diferentes trajetórias de risco cardiovascular (RCV) de 30 anos e seus fatores independentemente associados em participantes do Estudo CUME, um estudo prospectivo com ex-alunos de universidades federais de Minas Gerais, Brasil. Este estudo incluiu 1.286 participantes que responderam aos questionários de linha de base (2016) e acompanhamento (2018 e 2020). As trajetórias de RCV, de acordo com o escore de Framingham, foram identificadas por modelagem de crescimento de classe latente com o uso do modelo normal censurado. A análise dos fatores independentemente associados a cada uma das trajetórias foi realizada por regressão logística multinomial. Foram identificadas três trajetórias de RCV: Baixo-Baixo (68,3%), Médio-Médio (26,2%) e Alto-Alto (5,5%). Sexo masculino, união estável e consumo moderado e alto de alimentos ultraprocessados foram positivamente associados às trajetórias de RCV Médio-Médio e Alto-Alto. Formação profissional e trabalhar em áreas não relacionadas à saúde foram positivamente associados à trajetória de RCV Médio-Médio, enquanto ser fisicamente ativo foi negativamente associado à trajetória de RCV Alto-Alto. Em conclusão, mais de um terço dos participantes apresentou trajetórias de RCV nas categorias Médio-Médio e Alto-Alto. Fatores modificáveis foram associados a essas trajetórias (consumo de alimentos e atividade física); assim, medidas de promoção da saúde podem evitar a manutenção ou a piora do RCV. Por outro lado, os fatores não modificáveis associados às trajetórias Médio-Médio e Alto-Alto (características sociodemográficas e laborais) permitem traçar o perfil das pessoas que devem ser monitoradas com mais cautela pelos serviços de saúde.

Resumen: Nuestro objetivo fue analizar las diferentes trayectorias de riesgo cardiovascular (RCV) de 30 años y sus factores asociados de forma independiente en participantes del Estudio CUME, un estudio prospectivo con exalumnos de universidades federales de Minas Gerais, Brasil. Este estudio incluyó a 1.286 participantes que completaron los cuestionarios de referencia (2016) y de seguimiento (2018 y 2020). Las trayectorias de RCV, según el índice de Framingham, se identificaron mediante el modelado de crecimiento de clase latente utilizando el modelo normal censurado. El análisis de los factores asociados de forma independiente a cada una de las trayectorias se realizó mediante regresión logística multinomial. Se identificaron tres trayectorias de RCV: Bajo-Bajo (68,3%), Medio-Medio (26,2%) y Alto-Alto (5,5%). El género masculino, la unión estable y el consumo moderado y alto de alimentos ultraprocesados se asociaron positivamente con las trayectorias de RCV Medio-Medio y Alto-Alto. La formación profesional y el trabajo en áreas no relacionadas con la salud se asociaron positivamente con la trayectoria de RCV Medio-Medio, mientras que la actividad física se asoció negativamente con la trayectoria de RCV Alto-Alto. En conclusión, más de la tercera parte de los participantes presentó trayectorias de RCV en las categorías Medio-Medio y Alto-Alto. A estas trayectorias se asociaron factores modificables (consumo de alimentos y actividad física); por lo tanto, las medidas de promoción de la salud pueden prevenir el mantenimiento o el empeoramiento del RCV. Por otra parte, los factores no modificables asociados a las trayectorias Medio-Medio y Alto-Alto (características sociodemográficas y laborales) permiten delinear el perfil de las personas que deben ser monitoreadas con más atención por los servicios de salud.

Assisted clustering of gene expression data using regulatory data from partially overlapping sets of individuals.

BACKGROUND: As omics measurements profiled on different molecular layers are interconnected, integrative approaches that incorporate the regulatory effect from multi-level omics data are needed. When the multi-level omics data are from the same individuals, gene expression (GE) clusters can be identified using information from regulators like genetic variants and DNA methylation. When the multi-level omics data are from different individuals, the choice of integration approaches is limited. METHODS: We developed an approach to improve GE clustering from microarray data by integrating regulatory data from different but partially overlapping sets of individuals. We achieve this through (1) decomposing gene expression into the regulated component and the other component that is not regulated by measured factors, (2) optimizing the clustering goodness-of-fit objective function. We do not require the availability of different omics measurements on all individuals. A certain amount of individual overlap between GE data and the regulatory data is adequate for modeling the regulation, thus improving GE clustering. RESULTS: A simulation study shows that the performance of the proposed approach depends on the strength of the GE-regulator relationship, degree of missingness, data dimensionality, sample size, and the number of clusters. Across the various simulation settings, the proposed method shows competitive performance in terms of accuracy compared to the alternative K-means clustering method, especially when the clustering structure is due mostly to the regulated component, rather than the unregulated component. We further validate the approach with an application to 8,902 Framingham Heart Study participants with data on up to 17,873 genes and regulation information of DNA methylation and genotype from different but partially overlapping sets of participants. We identify clustering structures of genes associated with pulmonary function while incorporating the predicted regulation effect from the measured regulators. We further investigate the over-representation of these GE clusters in pathways of other diseases that may be related to lung function and respiratory health. CONCLUSION: We propose a novel approach for clustering GE with the assistance of regulatory data that allowed for different but partially overlapping sets of individuals to be included in different omics data.

Defining preventive cardiology: A clinical practice statement from the American Society for Preventive Cardiology.

Remarkable transformations in science and healthcare have resulted in declines in mortality from cardiovascular disease over the past several decades, largely driven by progress in prevention and treatment of persons at risk. However, these trends are now beginning to stall, as our county faces increases in cardiovascular risk factors including overweight and obesity, type 2 diabetes mellitus, and metabolic syndrome. Furthermore, poor long-term adherence to a healthy lifestyle and lifesaving pharmacotherapy have exacerbated these trends, with recent data suggesting unprecedented increases in cardiovascular morbidity and mortality. A paradigm shift is needed to improve the cardiovascular health of our nation. Preventive cardiology, a growing subspecialty of cardiovascular medicine, is the practice of primordial, primary, and secondary prevention of all cardiovascular diseases. Preventive cardiologists and preventive cardiology specialists are well equipped with the knowledge and skill-set necessary to reduce deaths related to the growing burden of heart disease and its risk factors. Despite dedicated efforts, cardiovascular disease remains the leading killer of men and women in the United States. Although there is little debate regarding the importance of prevention, many healthcare professionals question the need for preventive cardiology as a distinct subspecialty. Additionally, the field's growth has been hampered by a lack of organization and standardization, and variability of training within programs across the country. The purpose of this document is to delineate the key attributes that define the field of preventive cardiology according to the American Society for Preventive Cardiology.

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach.

INTRODUCTION: Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. METHODS: A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects' neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants' demographic characteristics. RESULTS: Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. DISCUSSION: The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.

Associations Between the Digital Clock Drawing Test and Brain Volume: Large Community-Based Prospective Cohort (Framingham Heart Study).

BACKGROUND: The digital Clock Drawing Test (dCDT) has been recently used as a more objective tool to assess cognition. However, the association between digitally obtained clock drawing features and structural neuroimaging measures has not been assessed in large population-based studies. OBJECTIVE: We aimed to investigate the association between dCDT features and brain volume. METHODS: This study included participants from the Framingham Heart Study who had both a dCDT and magnetic resonance imaging (MRI) scan, and were free of dementia or stroke. Linear regression models were used to assess the association between 18 dCDT composite scores (derived from 105 dCDT raw features) and brain MRI measures, including total cerebral brain volume (TCBV), cerebral white matter volume, cerebral gray matter volume, hippocampal volume, and white matter hyperintensity (WMH) volume. Classification models were also built from clinical risk factors, dCDT composite scores, and MRI measures to distinguish people with mild cognitive impairment (MCI) from those whose cognition was intact. RESULTS: A total of 1656 participants were included in this study (mean age 61 years, SD 13 years; 50.9% women), with 23 participants diagnosed with MCI. All dCDT composite scores were associated with TCBV after adjusting for multiple testing (P value <.05/18). Eleven dCDT composite scores were associated with cerebral white matter volume, but only 1 dCDT composite score was associated with cerebral gray matter volume. None of the dCDT composite scores was associated with hippocampal volume or WMH volume. The classification model for differentiating MCI and normal cognition participants, which incorporated age, sex, education, MRI measures, and dCDT composite scores, showed an area under the curve of 0.897. CONCLUSIONS: dCDT composite scores were significantly associated with multiple brain MRI measures in a large community-based cohort. The dCDT has the potential to be used as a cognitive assessment tool in the clinical diagnosis of MCI.

Association of a wide range of chronic diseases and apolipoprotein E4 genotype with subsequent risk of dementia in community-dwelling adults: A retrospective cohort study.

Background: Identifying independent and interactive associations of a wide range of diseases and multimorbidity and apolipoprotein E4 (APOE4) with dementia may help promote cognitive health. The main aim of the present study was to investigate associations of such diseases and their multimorbidity with incident dementia. Methods: In this retrospective cohort study, we included 471,485 individuals of European ancestry from the UK Biobank, aged 38-73 years at baseline (2006-10). Dementia was identified using inpatient records and death registers. The follow-up period was between March 16, 2006, and Jan 31, 2021. Findings: During a median follow-up of 11·9 years, 6189 cases of incident all-cause dementia (503 young-onset cases, 5686 late-onset cases) were documented. In multivariable-adjusted analysis, 33 out of 63 major diseases were associated with an increased risk of dementia. The hazard ratio (HR [95% CI]) ranged from 1·12 (1·06-1·19) for obesity to 14·22 (12·33-16·18) for Parkinson's disease. In addition to conventional diseases, respiratory disorders, musculoskeletal disorders, digestive disorders, painful conditions, and chronic kidney disease were associated with increased dementia risk. A larger HR for dementia was observed for a larger number of diseases (3·97 [3·51-4·48] for ≥6 diseases versus no disease). These individual diseases and multimorbidity were more predictive of young-onset dementia than of late-onset dementia. Dementia risk score incorporating multimorbidity, age, and APOE4 status had strong prediction performance (area under the curve [95% CI]: 82·2% [81·7-82·7%]). APOE4 was more predictive of late-onset dementia (HR [95% CI]: 2·90 [2·75-3·06]) than of young-onset dementia (1·26 [1·03-1·54]). Associations of painful conditions, depression, obesity, diabetes, stroke, Parkinson's disease, high cholesterol, and their multimorbidity with incident dementia were stronger among non-APOE4 carriers. Interpretation: Besides conventional diseases, numerous diseases are associated with an increased risk of dementia. These individual diseases and multimorbidity are more predictive of young-onset dementia, whereas APOE4 is more predictive of late-onset dementia. Individual diseases and multimorbidity are stronger predictors of dementia in non-APOE4 carriers. Although multiple risk factors have been adjusted for in the analysis, potential confounding from unknown factors may have biased the associations. Funding: The Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075), Science and Technology Program of Guangzhou, China (202,002,020,049).

A genomic approach identifies sRAGE as a putatively causal protein for asthma.

BACKGROUND: Asthma is a complex respiratory condition caused by environmental and genetic factors. Although lower concentrations of the anti-inflammatory protein soluble receptor for advanced glycation end products (sRAGE) have been associated with asthma in humans and mouse models, it is uncertain whether sRAGE plays a causal role in asthma. OBJECTIVE: We designed a 2-stage study of sRAGE in relation to asthma with association analysis in FHS participants as well as causal inference testing using Mendelian randomization (MR). METHODS: We measured plasma levels of sRAGE and performed cross-sectional analysis to examine the association between plasma sRAGE concentration and asthma status in 6546 FHS participants. We then used sRAGE protein advanced glycation end products (pQTLs) derived from a genome-wide association study of plasma sRAGE levels in ∼7000 FHS participants with UK Biobank asthma genome-wide association study in MR to consider sRAGE as a putatively causal protein for asthma. We also performed replication MR using an externally derived sRAGE pQTL from the INTERVAL study. Last, we conducted colocalization using cis-pQTL variants at the advanced glycosylation end-product specific receptor (AGER) locus with variants from the UK Biobank asthma genome-wide association study. RESULTS: Association analysis revealed that each 1 SD increment in sRAGE concentration was associated with a 14% lower odds of asthma in FHS participants (95% CI 0.76-0.96). MR identified sRAGE as putatively causal for and protective against asthma on the basis of self-reported (odds ratio [per 1 SE increment in inverse-rank-normalized sRAGE] = 0.97, 95% CI 0.95-0.99; P = .005) and doctor-diagnosed asthma (odds ratio = 0.97, 95% CI 0.95-0.99; P = .011). CONCLUSION: Through this genomic approach, we identified sRAGE as a putatively causal, biologically important, and protective protein in relation to asthma. Functional studies in cell/animal models are needed to confirm our findings.

Is dietary choline intake related to dementia and Alzheimer's disease risks? Results from the Framingham Heart Study.

BACKGROUND: The positive association of choline for cognition has been reported in both animal and human studies, yet the associations of choline with the risks of incident dementia or Alzheimer's disease (AD) in humans is unclear. OBJECTIVES: Our objective was to test the hypothesis that lower or higher dietary choline intake is associated with increased or decreased, respectively, risks of incident dementia and AD. METHODS: Data from the Framingham Heart Study Offspring Cohort exam 5 to exam 9 were used. Participants were free of dementia and stroke, with a valid self-reported 126-item Harvard FFQ at exam 5. The intakes of total choline, its contributing compounds, and betaine were estimated based on a published nutrient database. The intakes were updated at each exam to represent the cumulative average intake across the 5 exams. The associations between dietary choline intakes and incident dementia and AD were examined in mixed-effect Cox proportional hazard models, adjusting for covariates. RESULTS: A total of 3224 participants (53.8% female; mean ± SD age, 54.5 ± 9.7 y) were followed up for a mean ± SD of 16.1 ± 5.1 y (1991-2011). There were 247 incident dementia cases, of which 177 were AD. Dietary choline intake showed nonlinear relationships with incident dementia and AD. After adjusting for covariates, low choline intake (defined as ≤ 219 and ≤ 215 mg/d for dementia and AD, respectively) was significantly associated with incident dementia and incident AD. CONCLUSIONS: Low choline intake was associated with increased risks of incident dementia and AD.