Joint Analyses of Longitudinal and Time-to-Event Data in Research on Aging: Implications for Predicting Health and Survival

A Look at Primary and Secondary Prevention in the Elderly: The Two Sides of the Same Coin

The global population is experiencing an aging trend; however, this increased longevity is not necessarily accompanied by improved health in older age. A significant consequence of this demographic shift is the rising prevalence of multiple chronic illnesses, posing challenges to healthcare systems worldwide. Aging is a major risk factor for multimorbidity, which marks a progressive decline in resilience and a dysregulation of multisystem homeostasis. Cardiovascular risk factors, along with aging and comorbidities, play a critical role in the development of heart disease. Among comorbidities, age itself stands out as one of the most significant risk factors for cardiovascular disease, with its prevalence and incidence notably increasing in the elderly population. However, elderly individuals, especially those who are frail and have multiple comorbidities, are under-represented in primary and secondary prevention trials aimed at addressing traditional cardiovascular risk factors, such as hypercholesterolemia, diabetes mellitus, and hypertension. There are concerns regarding the optimal intensity of treatment, taking into account tolerability and the risk of drug interactions. Additionally, uncertainty persists regarding therapeutic targets across different age groups. This article provides an overview of the relationship between aging and cardiovascular disease, highlighting various cardiovascular prevention issues in the elderly population.

Forecasting prevalence and mortality of Alzheimer's disease using the partitioning models

OBJECTIVES

Health forecasting is an important aspect of ensuring that the health system can effectively respond to the changing epidemiological environment. Common models for forecasting Alzheimer's disease and related dementias (AD/ADRD) are based on simplifying methodological assumptions, applied to limited population subgroups, or do not allow analysis of medical interventions. This study uses 5 %-Medicare data (1991-2017) to identify, partition, and forecast age-adjusted prevalence and incidence-based mortality of AD as well as their causal components.

METHODS

The core underlying methodology is the partitioning analysis that calculates the relative impact each component has on the overall trend as well as intertemporal changes in the strength and direction of these impacts. B-spline functions estimated for all parameters of partitioning models represent the basis for projections of these parameters in future.

RESULTS

Prevalence of AD is predicted to be stable between 2017 and 2028 primarily due to a decline in the prevalence of pre-AD-diagnosis stroke. Mortality, on the other hand, is predicted to increase. In all cases the resulting patterns come from a trade-off of two disadvantageous processes: increased incidence and disimproved survival. Analysis of health interventions demonstrates that the projected burden of AD differs significantly and leads to alternative policy implications.

DISCUSSION

We developed a forecasting model of AD/ADRD risks that involves rigorous mathematical models and incorporation of the dynamics of important determinative risk factors for AD/ADRD risk. The applications of such models for analyses of interventions would allow for predicting future burden of AD/ADRD conditional on a specific treatment regime.

An immune-based biomarker signature is associated with mortality in COVID-19 patients

Immune and inflammatory responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contribute to disease severity of coronavirus disease 2019 (COVID-19). However, the utility of specific immune-based biomarkers to predict clinical outcome remains elusive. Here, we analyzed levels of 66 soluble biomarkers in 175 Italian patients with COVID-19 ranging from mild/moderate to critical severity and assessed type I IFN-, type II IFN-, and NF-κB-dependent whole-blood transcriptional signatures. A broad inflammatory signature was observed, implicating activation of various immune and nonhematopoietic cell subsets. Discordance between IFN-α2a protein and IFNA2 transcript levels in blood suggests that type I IFNs during COVID-19 may be primarily produced by tissue-resident cells. Multivariable analysis of patients' first samples revealed 12 biomarkers (CCL2, IL-15, soluble ST2 [sST2], NGAL, sTNFRSF1A, ferritin, IL-6, S100A9, MMP-9, IL-2, sVEGFR1, IL-10) that when increased were independently associated with mortality. Multivariate analyses of longitudinal biomarker trajectories identified 8 of the aforementioned biomarkers (IL-15, IL-2, NGAL, CCL2, MMP-9, sTNFRSF1A, sST2, IL-10) and 2 additional biomarkers (lactoferrin, CXCL9) that were substantially associated with mortality when increased, while IL-1α was associated with mortality when decreased. Among these, sST2, sTNFRSF1A, IL-10, and IL-15 were consistently higher throughout the hospitalization in patients who died versus those who recovered, suggesting that these biomarkers may provide an early warning of eventual disease outcome.

Genetics of physiological dysregulation: findings from the long life family study using joint models

Recently, Mahalanobis distance (D_M) was suggested as a statistical measure of physiological dysregulation in aging individuals. We constructed D_M variants using sets of biomarkers collected at the two visits of the Long Life Family Study (LLFS) and performed joint analyses of longitudinal observations of D_M and follow-up mortality in LLFS using joint models. We found that D_M is significantly associated with mortality (hazard ratio per standard deviation: 1.31 [1.16, 1.48] to 2.22 [1.84, 2.67]) after controlling for age and other covariates. GWAS of random intercepts and slopes of D_M estimated from joint models found a genome-wide significant SNP (rs12652543, p=7.2×10^-9) in the TRIO gene associated with the slope of D_M constructed from biomarkers declining in late life. Review of biological effects of genes corresponding to top SNPs from GWAS of D_M slopes revealed that these genes are broadly involved in cancer prognosis and axon guidance/synapse function. Although axon growth is mainly observed during early development, the axon guidance genes can function in adults and contribute to maintenance of neural circuits and synaptic plasticity. Our results indicate that decline in axons' ability to maintain complex regulatory networks may potentially play an important role in the increase in physiological dysregulation during aging.

The Alzheimer's Disease Exposome

INTRODUCTION

Environmental factors are poorly understood in the etiology of Alzheimer's disease (AD) and related dementias. The importance of environmental factors in gene environment interactions (GxE) is suggested by wide individual differences in cognitive loss, even for carriers of AD-risk genetic variants.

RESULTS AND DISCUSSION

We propose the "AD exposome" to comprehensively assess the modifiable environmental factors relevant to genetic underpinnings of cognitive aging and AD. Analysis of endogenous and exogenous environmental factors requires multi-generational consideration of these interactions over age and time (GxExT). New computational approaches to the multi-level complexities may identify accessible interventions for individual brain aging. International collaborations on diverse populations are needed to identify the most relevant exposures over the life course for GxE interactions.

Eighteen-year alcohol consumption trajectories and their association with risk of type 2 diabetes and its related factors: the China Health and Nutrition Survey

AIMS/HYPOTHESIS

Alcohol consumption levels frequently fluctuate over the life course, but studies examining the association between alcohol consumption trajectories and type 2 diabetes are limited. This study aims to investigate the association of alcohol consumption trajectories with the risk of type 2 diabetes and its related factors.

METHODS

Weighted longitudinal data were obtained for 12,186 adults who completed a questionnaire about alcohol consumption and diabetes status as part of the China Health and Nutrition Survey (1993-2011). Participants were designated into subgroups based on alcohol consumption trajectory, and subgroup analyses included 5436 individuals who were tested for specified diabetes-related factors. Light alcohol consumption was defined as fewer than seven standard drinks per week; moderate as 7-21 drinks per week; and heavy as more than 21 drinks per week. Latent class trajectory modelling was used to identify different alcohol consumption trajectories by sex. Multivariate Cox regression models and general linear regression models were used to assess association of trajectories with type 2 diabetes and its related factors.

RESULTS

Compared with stable abstainers (individuals who never drank alcohol), two trajectories in men showing reduction to moderate or light levels after heavy alcohol consumption during early adulthood were significantly associated with increased risk of type 2 diabetes (HR 1.66 [95% CI 1.18, 2.33]; HR 1.93 [95% CI 1.01, 3.70]), while no significant association between trajectories and risk of type 2 diabetes was observed in women (p _{for trend} = 0.404). Triacylglycerol, HDL-cholesterol (HDL-C), uric acid and high sensitivity C-reactive protein were significantly higher in these two trajectories than other trajectories in men (all p < 0.05), while only HDL-C showed significant increasing trends in women. Trajectories showing light-stable, or increase to moderate, levels were not associated with reduced risk of type 2 diabetes.

CONCLUSIONS

This study indicated that heavy alcohol consumption in early adulthood is significantly associated with increased risk of type 2 diabetes and higher levels of its biomarkers throughout adulthood in men. Gradually reducing alcohol consumption to moderate levels may not make a difference, which demonstrates the importance of alcohol intervention strategies in early adulthood. Although association between alcohol consumption and increased HDL-C levels has been observed, the results of this study did not support the hypothesis regarding the protective effect of moderate alcohol consumption on risk of type 2 diabetes in the Asian population.

DATA AVAILABILITY

Data from China Health and Nutrition Survey was used in this study, which can be downloaded at www.cpc.unc.edu/projects/china .

Association of thirty-year alcohol consumption typologies and fatty liver: Findings from a large population cohort study

OBJECTIVE

To evaluate the longitudinal relationship between repeated measures of alcohol consumption and risk of developing fatty liver.

PATIENTS AND METHODS

This study includes 5407 men and women from a British population-based cohort, the Whitehall II study of civil servants, who self-reported alcohol consumption by questionnaire over approximately 30 years (1985-1989 through to 2012-2013). Drinking typologies during midlife were linked to measures of fatty liver (the fatty liver index, FLI) when participants were in older age (age range 60-84 years) and adjusted for age, socio-economic position, ethnicity, and smoking.

RESULTS

Those who consistently drank heavily had two-fold higher odds of increased FLI compared to stable low-risk moderate drinkers after adjustment for covariates (men: OR = 2.04, 95%CI = 1.53-2.74; women: OR = 2.24, 95%CI = 1.08-4.55). Former drinkers also had an increased FLI compared to low-risk drinkers (men: OR = 2.09, 95%CI = 1.55-2.85; women: OR = 1.68, 95%CI = 1.08-2.67). There were non-significant differences in FLI between non-drinkers and stable low-risk drinkers. Among women, there was no increased risk for current heavy drinkers in cross sectional analyses.

CONCLUSION

Drinking habits among adults during midlife affect the development of fatty liver, and sustained heavy drinking is associated with an increased FLI compared to stable low-risk drinkers. After the exclusion of former drinkers, there was no difference between non-drinkers and low-risk drinkers, which does not support a protective effect on fatty liver from low-risk drinking. Cross-sectional analyses among women did not find an increased risk of heavy drinking compared to low-risk drinkers, thus highlighting the need to take a longitudinal approach.

A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data

Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases. This model is characterized by more profound biological interpretation and takes into account the dynamics of biomarkers during follow-up when investigating the hazards of a disease. We illustrate the rationale and evaluate the performance of the proposed model through two GWAS. One is to detect single nucleotide polymorphisms (SNPs) having interaction effects on type 2 diabetes (T2D) with body mass index (BMI) and the other is to detect SNPs affecting the optimal BMI level for protecting from T2D. We identified multiple SNPs that showed interaction effects with BMI on T2D, including a novel SNP rs11757677 in the CDKAL1 gene (P = 5.77 × 10-7 ). We also found a SNP rs1551133 located on 2q14.2 that reversed the effect of BMI on T2D (P = 6.70 × 10-7 ). In conclusion, the proposed GSPM provides a promising and useful tool in GWAS of longitudinal data for interrogating pleiotropic and interaction effects to gain more insights into the relationship between genes, quantitative biomarkers, and risks of complex diseases.

stpm: an R package for stochastic process model

BACKGROUND

The Stochastic Process Model (SPM) represents a general framework for modeling the joint evolution of repeatedly measured variables and time-to-event outcomes observed in longitudinal studies, i.e., SPM relates the stochastic dynamics of variables (e.g., physiological or biological measures) with the probabilities of end points (e.g., death or system failure). SPM is applicable for analyses of longitudinal data in many research areas; however, there are no publicly available software tools that implement this methodology.

RESULTS

We developed an R package stpm for the SPM-methodology. The package estimates several versions of SPM currently available in the literature including discrete- and continuous-time multidimensional models and a one-dimensional model with time-dependent parameters. Also, the package provides tools for simulation and projection of individual trajectories and hazard functions.

CONCLUSION

In this paper, we present the first software implementation of the SPM-methodology by providing an R package stpm, which was verified through extensive simulation and validation studies. Future work includes further improvements of the model. Clinical and academic researchers will benefit from using the presented model and software. The R package stpm is available as open source software from the following links: https://cran.r-project.org/package=stpm (stable version) or https://github.com/izhbannikov/spm (developer version).

Twenty-year trajectories of alcohol consumption during midlife and atherosclerotic thickening in early old age: findings from two British population cohort studies

BACKGROUND

Epidemiological evidence indicates a protective effect of light-moderate drinking on cardiovascular disease and an increased risk for heavier drinking. Nevertheless, the effect of alcohol on atherosclerotic changes in vessel walls is disputed. Most previous studies have only looked at the cross-sectional relationship between alcohol and carotid intima media thickness (cIMT) - a surrogate marker of atherosclerosis. Single measurements of alcohol assume that alcohol exposure is stable and ignore the possible cumulative effects of harm, leading to possibly incorrect inferences.

METHODS

Data were retrieved from two UK population based cohort studies: the Whitehall II cohort of civil servants and the MRC National Survey of Health and Development (combined sample size of 5403 men and women). Twenty year-drinking trajectories during midlife were linked to measures of cIMT when participants were in early old age, and adjusted for age, sex, socioeconomic position, ethnicity and smoking.

RESULTS

Those who consistently drank heavily had an increased cIMT compared to stable moderate drinkers (pooled difference in cIMT 0.021 mm; 95 % CI 0.002 to 0.039), after adjustment for covariates. This was not detected in cross-sectional analyses. Former drinkers also had an increased cIMT compared to moderate drinkers (pooled difference in cIMT 0.021; 95 % CI 0.005 to 0.037). There were no appreciable differences in cIMT between non-drinkers and consistent moderate drinkers.

CONCLUSION

The drinking habits among adults during midlife affect the atherosclerotic process and sustained heavy drinking is associated with an increased cIMT compared to stable moderate drinkers. This finding was not seen when only using cross-sectional analyses, thus highlighting the importance of taking a life course approach. There was no evidence of a favourable atherosclerotic profile from stable moderate drinking compared to stable non-drinking.

Dynamics of biomarkers in relation to aging and mortality

Contemporary longitudinal studies collect repeated measurements of biomarkers allowing one to analyze their dynamics in relation to mortality, morbidity, or other health-related outcomes. Rich and diverse data collected in such studies provide opportunities to investigate how various socio-economic, demographic, behavioral and other variables can interact with biological and genetic factors to produce differential rates of aging in individuals. In this paper, we review some recent publications investigating dynamics of biomarkers in relation to mortality, which use single biomarkers as well as cumulative measures combining information from multiple biomarkers. We also discuss the analytical approach, the stochastic process models, which conceptualizes several aging-related mechanisms in the structure of the model and allows evaluating "hidden" characteristics of aging-related changes indirectly from available longitudinal data on biomarkers and follow-up on mortality or onset of diseases taking into account other relevant factors (both genetic and non-genetic). We also discuss an extension of the approach, which considers ranges of "optimal values" of biomarkers rather than a single optimal value as in the original model. We discuss practical applications of the approach to single biomarkers and cumulative measures highlighting that the potential of applications to cumulative measures is still largely underused.

Genetics of aging, health, and survival: dynamic regulation of human longevity related traits

Background: The roles of genetic factors in human longevity would be better understood if one can use more efficient methods in genetic analyses and investigate pleiotropic effects of genetic variants on aging and health related traits.

Data and methods: We used EMMAX software with modified correction for population stratification to perform genome wide association studies (GWAS) of female lifespan from the original FHS cohort. The male data from the original FHS cohort and male and female data combined from the offspring FHS cohort were used to confirm findings. We evaluated pleiotropic effects of selected genetic variants as well as gene-smoking interactions on health and aging related traits. Then we reviewed current knowledge on functional properties of genes related to detected variants.

Results: The eight SNPs with genome-wide significant variants were negatively associated with lifespan in both males and females. After additional QC, two of these variants were selected for further analyses of their associations with major diseases (cancer and CHD) and physiological aging changes. Gene-smoking interactions contributed to these effects. Genes closest to detected variants appear to be involved in similar biological processes and health disorders, as those found in other studies of aging and longevity e.g., in cancer and neurodegeneration.

Conclusions: The impact of genes on longevity may involve trade-off-like effects on different health traits. Genes that influence lifespan represent various molecular functions but may be involved in similar biological processes and health disorders, which could contribute to genetic heterogeneity of longevity and the lack of replication in genetic association studies.