Time as an indispensable causal dimension in cardiovascular diseases: toward a four-dimensional biology

Heart failure (HF) exhibits distinctive event-and time-dependent patterns in incidence and progression dynamics. Over time, the heart first undergoes (mal)adaptive cellular, tissue and molecular remodelling 1,2. These alterations precede clinical symptoms and diagnosis 3,4 and reflect age-related changes in cardiovascular structure and function that lower the threshold for overt disease 4,5. This subclinical process is followed by incremental cardiac remodelling, including cardiac hypertrophy 6,7, myocardial stiffening 8, and impaired diastolic filling 4. Similar preclinical alterations occur across other cardiovascular and cardiometabolic disorders: atrial fibrosis and mitochondrial remodelling may develop before atrial fibrillation 9,10, endothelial dysfunction precedes hypertension and atherosclerosis 11 and even rare diseases such as J-wave syndromes are now considered cardiomyopathies with subtle structural abnormalities that remain undetected by standard imaging techniques 12. In addition, disturbances in protein homeostasis and metabolic adaptation occur long before the onset of clinical manifestations of the disease 13. Thus, sudden cardiac pathological events are often preceded by manifestations of biological processes that have been unfolding over several years. The temporal trajectories differ markedly across various pathologies 12,14, are not linear 15, and are modulated by age, sex, lifestyle and inter-organ interactions. This interindividual variability calls for a personalised temporal framework for diagnosis and therapy, rather than a single, universally applied diagnostic threshold. Disease is typically defined once a threshold value is exceeded 4. In HF, this heterogeneity is further reflected in the attempts to subcategorize distinct phenotypes, notably HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and HF with preserved ejection fraction (HFpEF). This differentiation likely represents overlapping but temporally and mechanistically divergent trajectories rather than strict separate entities 16. Similarly, this limitation is evident in the study and management of AF, where the conventional classification into paroxysmal and persistent forms, subsequently expanded to include long-standing persistent and permanent AF, fails to adequately capture individual risk profiles and the progressive nature of the underlying atrial myopathy 17. Emerging approaches based on biomarkers 18 and wearable or implantable devices 19,20 will increasingly enable realtime monitoring of individual disease trajectories for earlier detection of warning signals before irreversible remodelling occurs. A central challenge is to identify the therapeutically actionable window during which pathological remodelling remains reversible in order to limit disease progression. This limitation highlights the constraints of traditional frameworks based on universally applied symptomatology, isolated criteria and therefore simple causal relationships that inform therapeutic options 21. Given that cardiovascular (patho)biology emerges from continuous interactions across molecular pathways, cells, tissues, and inter-organ communication 21,22, cardiovascular diseases can be approached as a dynamic, multi-scale and complex trajectory extending from molecular networks to whole-organ function. However, even apparently linear causal relationships at the organ level are grounded in nonlinear molecular and cellular dynamics, highlighting the need for a multi-scale temporal framework. This trajectory is shaped against the background of biological aging and the dynamics of complex systems. This perspective requires a multidimensional framework in which time is considered an essential dimension of disease. Time is not only a static background information, but through aging it is also an active determinant of adaptation, remodelling, and failure. It should be note that the term "four-dimensional" has previously been used in cardiovascular cronobiology to describe the circadian regulation of cardiac physiology across an hourly-to-daily timescale 23,24. Here, however, the fourth dimension captures the longitudinal trajectory of disease development and biological aging over years. These represent distinct temporal scales and conceptual frameworks. Here, we argue that incorporating temporal biology into cardiovascular research, from molecular clocks to organlevel remodelling trajectories, is essential to advance precision cardiology and to identify therapeutically relevant temporal windows prior to the point of no return.In medicine, diagnosis is typically established when a physiological parameter deviates from a defined normal range. For example, hypertension is diagnosed when blood pressure exceeds a fixed numerical value, whereas HF is defined once the ejection fraction falls below a critical value 25. HFrEF (EF <40%), HFmrEF (EF 40-49%) and HFpEF (EF ≥50%) represent 3 clinical phenotypes 16 that share common pathophysiological mechanisms, neurohormonal modulation, myocardial fibrosis and inflammation, but differ in their temporal trajectories which may be influenced by major clinical events such as myocardial infarction, as well as in their therapeutic responses. These diagnostic thresholds define disease at the moment of clinical recognition rather than at its biological origin, reinforcing the perception that health ends and disease begins at the time of diagnosis rather than long before the clinical manifestation. This reflects a conceptual limitation: disease is anchored to clinical detection rather than to the underlying biological and time-dependent trajectory. Furthermore, diagnostic thresholds are often based on normal values established in relation to chronological age even though the cardiovascular system may be biologically much older or younger. For instance, the coronary endothelium of a 50year-old patient may exhibit a molecular signature typically observed in ol