“Cradle-to-grave” disease trajectories could help identify critical events that lead to the diagnosis of a particular condition many decades later, a study suggests.
The research could help integrate a person’s particular pathway in life into clinical decision-making, say the investigators.
The findings, in the Nature journal npj Digital Medicine, could also contribute to successful aging by identifying events that lead to rapid deterioration in health.
“We wanted to find out which typical disease trajectories occur in multimorbid patients from birth to death and which critical moments in their lives significantly shape the further course,” explained Elma Dervic, PhD, from the Complexity Science Hub research center in Vienna.
“This provides clues for very early and personalized prevention strategies.”
Multiple, often chronic, diseases commonly occur among individual patients and today’s reality of a 100-year lifespan brings an increase in this multimorbidity.
In the current study, Dervic and colleagues examined a dataset containing 44 million records comprising nearly all hospital stays in Austria between 2003 and 2014.
They then constructed multi-layered networks, with each layer representing a decade of life and different nodes corresponding to diagnoses within these layers.
Intralayer links identified co-occurring diseases and interlayer links showed which diagnosis tended to occur first. An algorithm identified overlapping communities in the multilayer network.
From this, Dervic and co-workers were able to identify correlations between various diseases in different age groups, such as how often obesity or hypertension occurred in a person’s 20s and the risk of other conditions occurring subsequently.
The team identified 126 distinct disease trajectories, including 618 in women and 642 in men, over an average period of 20 to 30 years but which could include up to 70 years of life in some cases.
“On average, one of these disease trajectories includes nine different diagnoses, highlighting how common multimorbidity actually is,” said Dervic.
There were 70 pairs of diverging trajectories that shared diagnoses at younger ages but developed into markedly different ones at people aged.
Critical events were identified as diagnosis combinations in a specific age group, mainly for chronic conditions, that signalled disease trajectories were about to diverge into paths leading to different levels of mortality or lengths of hospital stays for the subsequent age groups.
For sleep disorders, the model showed two typical trajectories for men aged 20 to 29 years.
One involved the later appearance of metabolic diseases such as diabetes mellitus, obesity, and lipid disorders. The other included movement disorders, among other conditions, which suggests organic sleep disorders could be an early marker for neurodegenerative diseases such as Parkinson’s disease.
Patients that followed the second trajectory tended to spend 9 days less in hospital while in their 20s but 29 days longer in their 30s and also suffered from more additional diagnoses.
Among girls aged 10 to 19 years with high blood pressure, while some went on to be diagnosed with additional metabolic diseases others experienced chronic kidney disease in their twenties that led to an increased risk of death at a young age.
“With these insights derived from real-life data, doctors can monitor various diseases more intensively and implement targeted, personalized preventive measures decades before serious problems arise,” said Dervic.
The findings also indicate that specific trajectories should receive more attention in clinical terms, the researchers say.
