Dmitry V. Kuznetsov

Psychosocial stress is a risk factor for aging-related diseases. The COVID-19 pandemic placed a psychosocial burden on individuals, potentially increasing the risk for aging-related diseases for which epigenetic clocks are used as early biomarkers. Based on four epigenetic clocks (DunedinPACE, GrimAge2, Horvath, and PedBE), we investigated whether epigenetic aging changed during the pandemic and whether these changes were associated with objective and subjective pandemic-related stressors and preexisting individual risk factors for poorer physical and mental health. We used prospective longitudinal data (n = 1,028), including repeated salivary DNA collection from children (n = 359, MAGE = 9.5 y), adolescents (n = 385, MAGE = 15.5 y), and adults (n = 284, MAGE = 24.3 y). Saliva was collected before the first phase of containment measures in Germany in March 2020 and after the second phase in 2021. We observed significant increases in epigenetic age acceleration (PedBE: b = 0.17, P < 0.0001; GrimAge2: b = 0.08, P < 0.0001) and pace of aging (DunedinPACE: b = 0.13, P < 0.0001) across all age groups. Prepandemic physical health and parental socioeconomic status, but not objective pandemic stressors, were significantly associated with this change. In adolescents, higher perceived pandemic burden was associated with a larger increase in pace of aging (DunedinPACE: b = 0.04, P = 0.01). Together, these findings suggest that prepandemic individual risk factors for poorer physical and mental health are accompanied by measurable increases in epigenetic aging during the COVID-19 pandemic, with adolescence representing a sensitive phase to its psychosocial burden.

Twin registries are foundational resources for research in behavioral and medical genetics, epidemiology, and public health. Over several decades, successive international reviews have documented their expansion in number, geographical coverage, phenotypic scope, molecular profiling, and participation in large-scale collaborations. This overview first traces this development through previous global overviews of twin registries and then examines record linkage as an increasingly important feature of contemporary twin research. Drawing on diverse twin registries, twin cohorts, multi-cohort resources, and international consortia, we describe how twin data are linked to population and administrative registers, health and educational records, biobanks, and environmental and geospatial data. Microdata linkage connects individual-level twin phenotypes with longitudinal administrative, clinical, educational, and molecular information, extending follow-up and supporting life-course analyses. Macrodata linkage incorporates contextual information on neighborhood environments, socioeconomic conditions, and policy settings, enabling individual and familial differences to be studied within broader social and environmental contexts. Comparison across resources demonstrates substantial variation in the scope and implementation of record linkage, from established national linkage systems to partial, domain-specific, and planned linkages, shaped by differences in legal frameworks, consent models, data governance, and secure access infrastructures. By placing current record linkage practices within the historical development of twin research resources, this overview shows how linkage extends the classical twin design through longitudinal, multi-domain, and contextual data, broadening its potential for research on health, behavior, and development across the life course.

To accompany the publication of the special issue, ‘Population-Level Data Linkages in Worldwide Twin Registries’, an online, interactive tool titled ‘Twin Registries Worldwide’ has been developed to provide an overview of twin registries across the globe. The tool currently offers a searchable table view that allows users to explore twin registries by country, registry name, recruitment period, sample size, phenotypic domains, availability of biological samples, and linkage to administrative or health-related databases.

Sensory Processing Sensitivity (SPS) describes a personality trait or a style of processing both external and internal inputs, ranging from very deep and reflective to shallow and quick. Variance in the components of SPS has been recently demonstrated to be attributable to both genetic and unique environmental factors, confirming the presence of stable biologically-influenced individual differences in SPS. Meanwhile, the knowledge of whether these estimates are replicable across other populations and whether particular factors may modulate the genetic-environmental architecture of SPS is limited. Thus, in the sample of 3455 German twins from the TwinLife twin registry (Nmonozygotic twins=1641, Ndizygotic twins=1814; Mage=18.17(4.89) years), we explored the structure and the degree of genetic and environmental contribution to SPS using a shorter version of the Hypersensitive Person Scale (HSP). We considered three subscales (EOE, Ease of excitation; LST, Lower sensitivity threshold; and AES, Aesthetic Sensitivity), and, further, examined whether the proportion of genetic (A) and environmental (E) variances varied between individuals in urban or rural environments.Approximately one third of the differences in the latent trait SPS (A:37%[30;43], E:(63%[57;70]) and its components were attributed to additive genetic factors, and the two thirds to unique environmental factors. Genetic and environmental factors tent to explain the shared variances within three subscales. For EOE, in contrast to the other subscales, genetic differences were slightly larger in urban areas (34%[28;40]) than in rural areas (30%[23;38]). The nature and development of SPS, the potential influence of living environment and the usefulness of the SPS for environmental neuroscience are, further, discussed.

Ambient air pollution, specifically particulate matter (PM10 and PM2.5), is a major environmental concern with well-documented links to health and life satisfaction. While the causal pathways and mechanisms underlying these associations are actively being researched, the contribution of genetic and environmental familial factors to these links remains largely unexplored. In this regard, emerging adulthood is intriguing, as young adults increasingly establish lives outside parental homes, allowing for greater separation of familial and individual-specific effects. To leverage this time window, we analysed data from 4,504 young adult twins in the TwinLife study (Mage=23.04 years, SD=0.82; Nmonozygotic=2,249; Ndizygotic=2,255), assessed up to six times between 2014 and 2022. Twin comparison analysis was used to decompose the population link between PM10 and life satisfaction to test whether the effect runs between families (between-pair) or within families (within-pair), and whether these effects are zygosity-, age-, and measurement-specific. The effect of PM10 on life satisfaction ran between families, suggesting that shared factors, such as indirect effects of familial SES or neighbourhood characteristics, may be of importance. In monozygotic twins, the between-pair negative effect of PM10 on life satisfaction strengthened with age (b=-0.006, SE=0.003) and year of measurement (b=-0.011, SE=0.004). Controlling for between-pair differences, the within-pair effect was significant within monozygotic twins (b=-0.088, SE=0.030), and not within dizygotic twins (b=0.006, SE=0.041), suggesting the possibility of genetic confounding and a small but quasi-causal relationship between PM10 and life satisfaction in young adulthood. Target interventions, thus, should include both addressing the specific factors shared by twin families and the development of emissions-reduction strategies.

Background: Psychosocial adversity (PSA) contributes to long-term health disparities and increased risk for non-communicable diseases. The effects of PSA arise through complex interactions between genes and the environment, which involve immune, endocrine, and epigenetic dysregulation. Methods: To examine how adversity affects mental and physical health via epigenetic alterations in a more controlled way, we examined the relationship between PSA and epigenetic aging in 28 monozygotic (MZ) twin pairs discordant for negative life experiences. Whole-blood DNA methylation (DNAm) profiling was performed using the Illumina Infinium EPIC v2 BeadChip array. Epigenetic age acceleration (EAA) was calculated using a panel of first to third-generation clocks, namely, Horvath, Hannum, PhenoAge (Levine), GrimAge (v2.0), Elastic Net and DunedinPACE. Results: Though we did not observe any significant group-level differences in epigenetic age acceleration between PSA and control at large, sex-stratified analyses revealed that PSA exposed males exhibited significant reductions in EAA compared to their co-twins when assessed using the Hannum, PhenoAge, and DunedinPACE clocks. In females, regression analyses showed significant positive associations between EAA and both negative life events and shame perception. Application of the dimensional model of adversity further revealed that psychosocial threat was strongly associated with increased EAA in females, whereas deprivation showed a weaker but significant association with EAA in males. These findings suggest a sex-specific and context-dependent biological response to PSA, potentially reflecting either adaptive or maladaptive epigenetic remodelling. Conclusion: The observed epigenetic age deceleration in PSA-exposed males, together with the associations between EAA and threat, shame perception, and life events in females, highlight the importance of context and perception in shaping sex-specific responses to adversity. Our results underscore the utility of MZ twin study designs in isolating psychosocial stress driven epigenetic effects and support DNAm clocks as biomarkers of stress-related biological aging. Overall, this study advances our understanding of the molecular underpinnings of social health inequalities and may inform future interventions aimed at promoting resilience and stress adaptation.

Personality stability and change are not only attributable to net contributions of genetic and environmental factors but also to their interplay. Environmental factors can accelerate or decelerate age-related changes in the expressions of genetic factors (i.e., epigenetic aging), which might influence personality change. Conversely, personality differences could drive experiential differences that accelerate or decelerate epigenetic aging. This study explored the associations between epigenetic aging and Big Five personality traits considering (sources of) stable and change differences. We analyzed saliva-based DNA methylation data on chronological and biological clocks and self-reported personality data from 1,088 early adolescent to young adult twins from two timepoints 2.3 years apart. (Biometric) latent change analyses revealed significant mean-level acceleration in epigenetic aging over time and decreases in personality traits except neuroticism, with variance in intraindividual changes mainly driven by environment. Acceleration in epigenetic aging based on chronological clocks was associated with higher baseline agreeableness and conscientiousness and decreases in conscientiousness. Epigenetic aging based on biological clocks and conscientiousness were negatively related at baseline. The links involving stable personality differences were rather genetic and the change correlation primarily environmental. Findings are discussed considering epigenetic aging and personality differences in a system of interacting genetic and environmental factors.

Life and social adversities experienced before adulthood are decisive drivers of later life health inequalities, which hinge on immune, endocrine and epigenetic changes that reflect an individual’s interaction with the environment. Since monozygotic (MZ) twins share the same genetic background and perinatal environment, they provide a robust approach to identify environmental influences on biological features while controlling genetic confounders. We screened MZ and dizygotic (DZ) twin pairs (aged of 17 to 32 years) from the German TwinLife study for recent and time-distant adversities in their psychosocial environment (PSE). Here, we present three statistical approaches we developed to quantify adverse experiences in 739 twin pairs (349 MZ, 390 DZ). We calculated divergence scores based on score differences between each twin pair. By combining these approaches, we identified adversity-divergent twins (144 MZ, 173 DZ), suggesting that in approximately 41% - 44% of twin pairs, there was a clear divergence in their adversarial experiences and how they interpreted their PSE. Variance modelling suggested that 43% of the adversity experienced by the twins was due to their unique environment, while 23% was from their shared environment while 33% of the variance was explained by genetic factors.

Background: Epigenetic aging estimators commonly track chronological and biological aging, quantifying its accumulation (i.e., epigenetic age acceleration) or speed (i.e., epigenetic aging pace). Their scores reflect a combination of inherent biological programming and the impact of environmental factors, which are suggested to vary at different life stages. The transition from adolescence to adulthood is an important period in this regard, marked by an increasing and, then, stabilizing epigenetic aging variance. Whether this pattern arises from environmental influences or genetic factors is still uncertain. This study delves into understanding the genetic and environmental contributions to variance in epigenetic aging across these developmental stages. Using twin modeling, we analyzed four estimators of epigenetic aging, namely Horvath Acceleration, PedBE Acceleration, GrimAge Acceleration, and DunedinPACE, based on saliva samples collected at two timepoints approximately 2.5 years apart from 976 twins of four birth cohorts (aged about 9.5, 15.5, 21.5, and 27.5 years at first and 12, 18, 24, and 30 years at second measurement occasion). Results: Half to two-thirds (50–68%) of the differences in epigenetic aging were due to unique environmental factors, indicating the role of life experiences and epigenetic drift, besides measurement error. The remaining variance was explained by genetic (Horvath Acceleration: 24%; GrimAge Acceleration: 32%; DunedinPACE: 47%) and shared environmental factors (Horvath Acceleration: 26%; PedBE Acceleration: 47%). The genetic and shared environmental factors represented the primary sources of stable differences in corresponding epigenetic aging estimators over 2.5 years. Age moderation analyses revealed that the variance due to individually unique environmental sources was smaller in younger than in older cohorts in epigenetic aging estimators trained on chronological age (Horvath Acceleration: 47–49%; PedBE Acceleration: 33–68%). The variance due to genetic contributions, in turn, potentially increased across age groups for epigenetic aging estimators trained in adult samples (Horvath Acceleration: 18–39%; GrimAge Acceleration: 24–43%; DunedinPACE: 42–57%). Conclusions: Transition to adulthood is a period of the increasing variance in epigenetic aging. Both environmental and genetic factors contribute to this trend. The degree of environmental and genetic contributions can be partially explained by the design of epigenetic aging estimators.