Longitudinal weight differences, gene expression and blood biomarkers in BMI-discordant identical twins

The association of overweight, obesity, and long-term obesity with SARS-CoV-2 infection: a meta-analysis of 9 population-based cohorts from the Netherlands Cohorts Consortium

BACKGROUND

Obesity may affect an individual's immune response and subsequent risk of infection, such as a SARS-CoV-2 infection. It is less clear whether overweight and long-term obesity also constitute risk factors. We investigated the association between the degree and duration of overweight and obesity and SARS-CoV-2 infection.

METHODS

We analyzed data from nine prospective population-based cohorts of the Netherlands Cohorts Consortium, with a total of 99,570 participants, following a standardized procedure. Body mass index (BMI) and waist circumference (WC) were assessed two times before the pandemic, with approximately 5 years between measurements. SARS-CoV-2 infection was defined by self-report as a positive PCR or rapid-antigen test or as COVID-19 ascertained by a physician between March 2020 and January 2023. For three cohorts, information on SARS-CoV-2 infection by serology was available. Results were pooled using random-effects meta-analyses and adjusted for age, sex, educational level, and number of SARS-CoV-2 infection measurements.

RESULTS

Individuals with overweight (25 ≤ BMI < 30 kg/m2) (odds ratio (OR) = 1.08, 95%-confidence interval (CI) 1.04-1.13) or obesity (BMI ≥ 30 kg/m2) (OR = 1.43, 95%-CI 1.18-1.75) were more likely to report SARS-CoV-2 infection than individuals with a healthy body weight. We observed comparable ORs for abdominal overweight (men: 94 cm≤WC < 102 cm, women: 80 cm≤WC < 88 cm) (OR = 1.09, 95%-CI 1.04-1.14, I2 = 0%) and abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) (OR = 1.24, 95%-CI 0.999-1.55, I2 = 57%). Individuals with obesity long before the pandemic, but with a healthy body weight or overweight just before the pandemic, were not at increased risk.

CONCLUSION

Overweight and obesity were associated with increased risk of SARS-CoV-2 infection with stronger associations for obesity. Individuals with a healthier weight prior to the pandemic but previous obesity did not have an increased risk of SARS-CoV-2, suggesting that weight loss in those with obesity reduces infection risk. These results underline the importance of obesity prevention and weight management for public health.

Effects of Obesity and Exercise on Hepatic and Pancreatic Lipid Content and Glucose Metabolism: PET Studies in Twins Discordant for BMI

Obesity and sedentarism are associated with increased liver and pancreatic fat content (LFC and PFC, respectively) as well as impaired organ metabolism. Exercise training is known to decrease organ ectopic fat but its effects on organ metabolism are unclear. Genetic background affects susceptibility to obesity and the response to training. We studied the effects of regular exercise training on LFC, PFC, and metabolism in monozygotic twin pairs discordant for BMI. We recruited 12 BMI-discordant monozygotic twin pairs (age 40.4, SD 4.5 years; BMI 32.9, SD 7.6, 8 female pairs). Ten pairs completed six months of training intervention. We measured hepatic insulin-stimulated glucose uptake using [18F]FDG-PET and fat content using magnetic resonance spectroscopy before and after the intervention. At baseline LFC, PFC, gamma-glutamyl transferase (GT), and hepatic glucose uptake were significantly higher in the heavier twins compared to the leaner co-twins (p = 0.018, p = 0.02 and p = 0.01, respectively). Response to training in liver glucose uptake and GT differed between the twins (Time*group p = 0.04 and p = 0.004, respectively). Liver glucose uptake tended to decrease, and GT decreased only in the heavier twins (p = 0.032). In BMI-discordant twins, heavier twins showed higher LFC and PFC, which may underlie the observed increase in liver glucose uptake and GT. These alterations were mitigated by exercise. The small number of participants makes the results preliminary, and future research with a larger pool of participants is warranted.

Polygenic risk of obesity and BMI trajectories over 36 years: A longitudinal study of adult Finnish twins

OBJECTIVE

This study investigated 36-year BMI trajectories in twins whose BMI in young adulthood was below, within, or above their genetically predicted BMI, with a focus on twin pairs with large intrapair BMI differences (within-pair ΔBMI ≥ 3 kg/m2 ).

METHODS

Together, 3227 like-sexed twin pairs (34% monozygotic) were examined at age ~30 years in 1975 and followed up in 1981, 1990, and 2011. An individual's observed BMI in 1975 was considered within (±2.0), below (<-2.0), or above (>+2.0) genetically predicted BMI, measured by a polygenic risk score of 996,919 single nucleotide polymorphisms.

RESULTS

In monozygotic and dizygotic twin pairs with large intrapair BMI differences, the co-twin with a higher observed BMI in 1975 deviated above predicted BMI more frequently (~2/3) than the co-twin with a lower BMI deviated below prediction (~1/3). Individuals below, within, and above prediction in 1975 reached, respectively, normal weight, overweight, and obesity by 2011, with a mean BMI increase of 4.5 (95% CI: 4.3-4.8).

CONCLUSIONS

Categorizing BMI as below, within, or above polygenic risk score-predicted BMI helps identifying individuals who have been resistant or susceptible to weight gain. This may provide new insights into determinants and consequences of obesity.

The Co-Twin Control Design: Implementation and Methodological Considerations

Establishing causal relationships in observational studies is an important step in research and policy decision making. The association between an exposure and an outcome can be confounded by multiple factors, often making it hard to draw causal conclusions. The co-twin control design (CTCD) is a powerful approach that allows for the investigation of causal effects while controlling for genetic and shared environmental confounding factors. This article introduces the CTCD and offers an overview of analysis methods for binary and continuous outcome and exposure variables. Tools for data simulation are provided, along with practical guidance and accompanying scripts for implementing the CTCD in R, SPSS, and Stata. While the CTCD offers valuable insights into causal inference, it depends on several assumptions that are important when interpreting CTCD results. By presenting a broad overview of the CTCD, this article aims to equip researchers with actionable recommendations and a comprehensive understanding of the design's strengths and limitations.

Genetic impacts on DNA methylation help elucidate regulatory genomic processes

BACKGROUND

Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk.

RESULTS

We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites).

CONCLUSIONS

Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .

Leveraging a genetically-informative study design to explore depression as a risk factor for type 2 diabetes: Rationale and participant characteristics of the Mood and Immune Regulation in Twins Study

Background

Comorbidity between depression and type 2 diabetes is thought to arise from the joint effects of psychological, behavioral, and biological processes. Studies of monozygotic twins may provide a unique opportunity for clarifying how these processes inter-relate. This paper describes the rationale, characteristics, and initial findings of a longitudinal co-twin study aimed at examining the biopsychosocial mechanisms linking depression and risk of diabetes in mid-life.

Methods

Participants in the Mood and Immune Regulation in Twins (MIRT) Study were recruited from the Mid-Atlantic Twin Registry. MIRT consisted of 94 individuals who do not have diabetes at baseline, representing 43 twin pairs (41 monozygotic and 2 dizygotic), one set of monozygotic triplets, and 5 individuals whose co-twin did not participate. A broad set of variables were assessed including psychological factors (e.g., lifetime history major depression (MD)); social factors (e.g., stress perceptions and experiences); and biological factors, including indicators of metabolic risk (e.g., BMI, blood pressure (BP), HbA1c) and immune functioning (e.g., pro- and anti-inflammatory cytokines), as well as collection of RNA. Participants were re-assessed 6-month later. Intra-class correlation coefficients (ICC) and descriptive comparisons were used to explore variation in these psychological, social, and biological factors across time and within pairs.

Results

Mean age was 53 years, 68% were female, and 77% identified as white. One-third had a history of MD, and 18 sibling sets were discordant for MD. MD was associated with higher systolic (139.1 vs 132.2 mmHg, p=0.05) and diastolic BP (87.2 vs. 80.8 mmHg, p=0.002) and IL-6 (1.47 vs. 0.93 pg/mL, p=0.001). MD was not associated with BMI, HbA1c, or other immune markers. While the biological characteristics of the co-twins were significantly correlated, all within-person ICCs were higher than the within-pair correlations (e.g., HbA1c within-person ICC=0.88 vs. within-pair ICC=0.49; IL-6 within-person ICC=0.64 vs. within-pair=0.54). Among the pairs discordant for MD, depression was not substantially associated with metabolic or immune markers, but was positively associated with stress.

Conclusions

Twin studies have the potential to clarify the biopsychosocial processes linking depression and diabetes, and recently completed processing of RNA samples from MIRT permits future exploration of gene expression as a potential mechanism.

Neurological Symptoms and Their Associations With Inflammatory Biomarkers in the Chronic Phase Following Traumatic Brain Injuries

BACKGROUND

The underlying biological mechanisms for neurological symptoms following a traumatic brain injury (TBI) remain poorly understood. This study investigated the associations between serum inflammatory biomarkers and neurological symptoms in the chronic phase following moderate to severe TBI.

METHODS

The serum interleukin [IL]-1β, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, and the tumor necrosis factor [TNF]-α in 72 TBI patients 6 months to 2 years post injury were measured. Neurological symptoms including depression, chronic headache, sleep disturbance, irritability, anxiety, and global neurological disability was assessed. The associations between the biomarkers and the neurological symptoms were assessed using correlation and regression analysis.

RESULTS

It was found that the most common post-injury symptom was sleep disturbance (84.7%), followed by chronic headaches (59.7%), irritability (55.6%), and depression (54.2%). TNF-α was a protective factor for chronic headache (OR = 0.473, 95% CI = 0.235-0.952). IL-6 was positively associated with sleep disturbance (r = 0.274, p = 0.021), while IL-5 and IL-12p70 were negatively associated with the degree of global neurological disability (r = -0.325, p = 0.006; r = -0.319, p = 0.007).

CONCLUSION

This study provides preliminary evidence for the association between chronic inflammation with neurological symptoms following a TBI, which suggests that anti-inflammatory could be a potential target for post-TBI neurological rehabilitation. Further research with larger sample sizes and more related biomarkers are still needed, however, to elucidate the inflammatory mechanisms for this association.

An integrative machine learning approach to discovering multi-level molecular mechanisms of obesity using data from monozygotic twin pairs

We combined clinical, cytokine, genomic, methylation and dietary data from 43 young adult monozygotic twin pairs (aged 22-36 years, 53% female), where 25 of the twin pairs were substantially weight discordant (delta body mass index > 3 kg m^-2). These measurements were originally taken as part of the TwinFat study, a substudy of The Finnish Twin Cohort study. These five large multivariate datasets (comprising 42, 71, 1587, 1605 and 63 variables, respectively) were jointly analysed using an integrative machine learning method called group factor analysis (GFA) to offer new hypotheses into the multi-molecular-level interactions associated with the development of obesity. New potential links between cytokines and weight gain are identified, as well as associations between dietary, inflammatory and epigenetic factors. This encouraging case study aims to enthuse the research community to boldly attempt new machine learning approaches which have the potential to yield novel and unintuitive hypotheses. The source code of the GFA method is publically available as the R package GFA.

RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation

Background

A gap exists in our mechanistic understanding of how genetic and environmental risk factors converge at the molecular level to result in the emergence of autism symptoms. We compared blood-based gene expression signatures in identical twins concordant and discordant for autism spectrum condition (ASC) to differentiate genetic and environmentally driven transcription differences, and establish convergent evidence for biological mechanisms involved in ASC.

Methods

Genome-wide gene expression data were generated using RNA-seq on whole blood samples taken from 16 pairs of monozygotic (MZ) twins and seven twin pair members (39 individuals in total), who had been assessed for ASC and autism traits at age 12. Differential expression (DE) analyses were performed between (a) affected and unaffected subjects (N = 36) and (b) within discordant ASC MZ twin pairs (total N = 11) to identify environmental-driven DE. Gene set enrichment and pathway testing was performed on DE gene lists. Finally, an integrative analysis using DNA methylation data aimed to identify genes with consistent evidence for altered regulation in cis.

Results

In the discordant twin analysis, three genes showed evidence for DE at FDR < 10%: IGHG4, EVI2A and SNORD15B. In the case-control analysis, four DE genes were identified at FDR < 10% including IGHG4, PRR13P5, DEPDC1B, and ZNF501. We find enrichment for DE of genes curated in the SFARI human gene database. Pathways showing evidence of enrichment included those related to immune cell signalling and immune response, transcriptional control and cell cycle/proliferation. Integrative methylomic and transcriptomic analysis identified a number of genes showing suggestive evidence for cis dysregulation.

Limitations

Identical twins stably discordant for ASC are rare, and as such the sample size was limited and constrained to the use of peripheral blood tissue for transcriptomic and methylomic profiling. Given these primary limitations, we focused on transcript-level analysis.

Conclusions

Using a cohort of ASC discordant and concordant MZ twins, we add to the growing body of transcriptomic-based evidence for an immune-based component in the molecular aetiology of ASC. Whilst the sample size was limited, the study demonstrates the utility of the discordant MZ twin design combined with multi-omics integration for maximising the potential to identify disease-associated molecular signals.

The Netherlands Twin Register: Longitudinal Research Based on Twin and Twin-Family Designs

The Netherlands Twin Register (NTR) is a national register in which twins, multiples and their parents, siblings, spouses and other family members participate. Here we describe the NTR resources that were created from more than 30 years of data collections; the development and maintenance of the newly developed database systems, and the possibilities these resources create for future research. Since the early 1980s, the NTR has enrolled around 120,000 twins and a roughly equal number of their relatives. The majority of twin families have participated in survey studies, and subsamples took part in biomaterial collection (e.g., DNA) and dedicated projects, for example, for neuropsychological, biomarker and behavioral traits. The recruitment into the NTR is all inclusive without any restrictions on enrollment. These resources - the longitudinal phenotyping, the extended pedigree structures and the multigeneration genotyping - allow for future twin-family research that will contribute to gene discovery, causality modeling, and studies of genetic and cultural inheritance.

Brain reward responses to food stimuli among female monozygotic twins discordant for BMI

Obese individuals are characterized by altered brain reward responses to food. Despite the latest discovery of obesity-associated genes, the contribution of environmental and genetic factors to brain reward responsiveness to food remains largely unclear. Sixteen female monozygotic twin pairs with a mean BMI discordance of 3.96 ± 2.1 kg/m² were selected from the Netherlands Twin Register to undergo functional MRI scanning while watching high- and low-calorie food and non-food pictures and during the anticipation and receipt of chocolate milk. In addition, appetite ratings, eating behavior and food intake were assessed using visual analog scales, validated questionnaires and an ad libitum lunch. In the overall group, visual and taste stimuli elicited significant activation in regions of interest (ROIs) implicated in reward, i.e. amygdala, insula, striatum and orbitofrontal cortex. However, when comparing leaner and heavier co-twins no statistically significant differences in ROI-activations were observed after family wise error correction. Heavier versus leaner co-twins reported higher feelings of hunger (P = 0.02), cravings for sweet food (P = 0.04), body dissatisfaction (P < 0.05) and a trend towards more emotional eating (P = 0.1), whereas caloric intake was not significantly different between groups (P = 0.3). Our results suggest that inherited rather than environmental factors are largely responsible for the obesity-related altered brain responsiveness to food. Future studies should elucidate the genetic variants underlying the susceptibility to reward dysfunction and obesity.

CLINICAL TRIAL REGISTRATION NUMBER

NCT02025595.

Metataxonomic Analysis of Individuals at BMI Extremes and Monozygotic Twins Discordant for BMI

OBJECTIVE

The human gut microbiota has been demonstrated to be associated with a number of host phenotypes, including obesity and a number of obesity-associated phenotypes. This study is aimed at further understanding and describing the relationship between the gut microbiota and obesity-associated measurements obtained from human participants.

SUBJECTS/METHODS

Here, we utilize genetically informative study designs, including a four-corners design (extremes of genetic risk for BMI and of observed BMI; N = 50) and the BMI monozygotic (MZ) discordant twin pair design (N = 30), in order to help delineate the role of host genetics and the gut microbiota in the development of obesity.

RESULTS

Our results highlight a negative association between BMI and alpha diversity of the gut microbiota. The low genetic risk/high BMI group of individuals had a lower gut microbiota alpha diversity when compared to the other three groups. Although the difference in alpha diversity between the lean and heavy groups of the BMI-discordant MZ twin design did not achieve significance, this difference was observed to be in the expected direction, with the heavier participants having a lower average alpha diversity. We have also identified nine OTUs observed to be associated with either a leaner or heavier phenotype, with enrichment for OTUs classified to the Ruminococcaceae and Oxalobacteraceae taxonomic families.

CONCLUSION

Our study presents evidence of a relationship between BMI and alpha diversity of the gut microbiota. In addition to these findings, a number of OTUs were found to be significantly associated with host BMI. These findings may highlight separate subtypes of obesity, one driven by genetic factors, the other more heavily influenced by environmental factors.

Association of current and former smoking with body mass index: A study of smoking discordant twin pairs from 21 twin cohorts

Background

Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background.

Methods and findings

The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18–69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m² lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m² lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m² higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/m² higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m², 95% CI 0.04, 0.23 among men; -0.04 kg/m², 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade.

Conclusions

Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m².

Rethinking IL-6 and CRP: Why they are more than inflammatory biomarkers, and why it matters

Behavioral researchers have increasingly become interested in the idea that chronic, low-grade inflammation is a pathway through which social and behavioral variables exert long-term effects on health. Much research in the area employs putative inflammatory biomarkers to infer an underlying state of inflammation. Interleukin 6 (IL-6) and C-reactive protein (CRP, whose production is stimulated by IL-6) are arguably the two most commonly assayed biomarkers. Yet, in contrast with near-universal assumptions in the field, discoveries in immunology over the past two decades show that neither IL-6 nor CRP are unambiguous inflammatory markers. IL-6 operates through two distinct signaling pathways, only one of which is specifically upregulated during inflammation; both pathways have a complex range of effects and influence multiple physiological processes even in absence of inflammation. Similarly, CRP has two isoforms, one of which is produced locally in inflamed or damaged tissues. The other isoform is routinely produced in absence of inflammation and may have net anti-inflammatory effects. We propose a functional framework to account for the multiple actions of IL-6 and CRP. Specifically, we argue that both molecules participate in somatic maintenance efforts; hence elevated levels indicate that an organism is investing in protection, preservation, and/or repair of somatic tissue. Depending on the state of the organism, maintenance may be channeled into resistance against pathogens (including inflammation), pathogen tolerance and harm reduction, or tissue repair. The findings and framework we present have a range of potential implications for the interpretation of empirical findings in this area-a point we illustrate with alternative interpretations of research on socioeconomic status, stress, and depression.

Overweight is associated with lower resting state functional connectivity in females after eliminating genetic effects: A twin study

Obesity is related to altered functional connectivity of resting state brain networks that are involved in reward and motivation. It is unknown to what extent these associations reflect genetic confounding and whether the obesity-related connectivity changes are associated with differences in dietary intake. In this study, resting state functional MRI was performed after an overnight fast in 16 female monozygotic twin pairs (aged 48.8 ± 9.8 years) with a mean BMI discordance of 3.96 ± 2.1 kg/m² (range 0.7-8.2). Functional connectivity of the salience, basal ganglia, default mode and anterior cingulate-orbitofrontal cortex networks was examined by independent component analysis. Dietary intake was assessed using 3-day 24-hour recalls. Results revealed that within the basal ganglia network, heavier versus leaner co-twins have decreased functional connectivity strength in bilateral putamen (P < 0.05, FWE-corrected). There were no differences in connectivity in the other networks examined. In the overall group, lower functional connectivity strength in the left putamen was correlated with higher intake of total fat (P < 0.01). It was concluded that, after eliminating genetic effects, overweight is associated with lower resting state functional connectivity in bilateral putamen in the basal ganglia network. The association between lower putamen connectivity and higher fat intake suggests an important role of the putamen in appetitive mechanisms. The cross-sectional nature of our study cannot discriminate cause and consequence, but the findings are compatible with an effect of lower putamen connectivity on increased BMI and associated higher fat intake. Hum Brain Mapp 38:5069-5081, 2017. © 2017 Wiley Periodicals, Inc.

Physical activity and dietary intake in BMI discordant identical twins

OBJECTIVE

Despite the latest discovery of obesity-associated genes, the rapid rise in global obesity suggests a major role for environmental factors. This study investigated the influence of environmental factors on physical activity and dietary intake independent of genetic effects.

METHODS

Sixteen female monozygotic twins aged 48.8 ± 9.8 years (range 37-70) with a mean BMI discordance of 3.96 ± 2.1 kg/m(2) (range 0.7-8.2) were studied. Physical activity was determined using 7-day accelerometry and dietary intake using 3-day 24-h recalls.

RESULTS

Heavier cotwins were generally less physically active (mean activity counts × 1,000 per day ± SD; 505.5 ± 155.1 vs. 579.6 ± 185.4, P = 0.047) and tended to spend 6.1 min/day less in moderate to vigorous physical activity than leaner cotwins (P = 0.09). Energy intake did not significantly differ within pairs. Total fat intake (en%; P = 0.03), specifically monounsaturated fat (P < 0.01) and polyunsaturated fat (P = 0.08), was higher in the heavier cotwins.

CONCLUSIONS

After eliminating genetic effects, higher BMI is associated with lower overall and moderate to vigorous physical activity and higher intake of total fat, although the direction of causality cannot be determined. Future identification of the environmental factors responsible for these findings might contribute to developing new strategies in managing obesity.

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.