As healthcare shifts focus from treatment to prediction – for the ultra-wealthy, at least – an opportunity presents itself: if risk can be identified early enough, can it be managed or even avoided altogether? Genome sequencing analyses an individual’s full DNA, revealing variations that may shape disease risk and treatment response. For wealthy clients, it can turn health uncertainty into something more controllable – identifying risks early and even having the chance to act on them.

For Carole, a Hong Kong-based finance professional who underwent genome sequencing more than a decade ago, curiosity ultimately won out. Even though she describes herself as a “late adopter and an early giver-upper”, the promise of what her DNA might reveal was difficult to ignore.

“I was curious to see what it turned up, but I found myself getting nervous about what it might uncover,” she says. “There was also the question of whether I really wanted to know what was lurking in my genetic code.”

The process involves analysing DNA from a saliva or blood sample – a simple enough process – and comparing it with large databases to identify genetic variations linked to disease risk and treatment response.

“In the end, my results showed surprisingly few mutations,” she says. “That has left me worrying I might live until I’m 105, like my great aunt – which could, in fact, be even worse.”

Her experience reflects a broader shift in approaches to healthcare. Advances in genomics are reshaping healthcare from a reactive system into a predictive and personalised model.

As regional genome projects scale up, clinicians are increasingly using genetic data to guide both diagnosis and therapy. Yet the effectiveness of these tools depends heavily on the data behind them.

“Most existing genomic reference data sets are heavily skewed toward European populations,” says Daniel Siu, CEO of Rainbow Genomics. “This creates real clinical limitations, as variants may be misclassified, and risk predictions may be less accurate for Asian individuals.”

Rainbow Genomics, which has operations in Hong Kong and San Francisco, has launched an Asian genomic database integrating genome sequencing, pharmacogenomics and clinical data from thousands of patients to improve how disease risk and other metrics are interpreted in populations in the region.

The aim of combining genetic data with detailed clinical profiles is to improve the accuracy of diagnosis and risk prediction, particularly as genetic testing moves beyond specialist settings into broader health planning. In addition to diagnosis, genetic testing can aid in day-to-day decisions.

A growing number of services now translate this information into lifestyle recommendations, from diet and exercise to sleep patterns and preventive screening. This so-called “precision living” approach has gained traction among younger wealthy clients already accustomed to tracking health metrics through wearable devices.

However, the scientific basis for some of these recommendations remains uneven. While certain gene-disease links are well established, others are still the subject of ongoing research, raising questions about how precisely lifestyle interventions can be tailored.

“I tried to adjust things after my results came in – what I was eating, how I exercised – but it’s not that easy to sustain,” says Carole.

Where genetic testing moves most clearly beyond lifestyle guidance is in its application to treatment, particularly in the emerging field of pharmacogenomics. This, combined with advances in data analysis, is also expanding how biological information is used in clinical decision-making.

Researchers at the University of Hong Kong (HKU) last month announced they had developed an artificial intelligence-based tool that integrates genetic, protein and metabolic data to predict cardiovascular risk years before symptoms appear.

“Genes determine where we start – they define our baseline health risk. However, proteins and metabolites reflect our current physical health,” says Zhang Qingpeng, associate professor in HKU’s department of pharmacology and pharmacy. “Our AI tool is designed to decode these signals, enabling doctors and patients to identify risks much earlier.” By analysing specific gene variants, clinicians can better understand how a patient metabolises certain drugs, helping to reduce adverse reactions and improve the medication’s effectiveness.

In practice, this can help avoid the trial-and-error approach that often characterises prescribing, particularly in areas such as mental health, oncology and cardiovascular disease. For patients, the impact can be immediate: genetic testing may indicate that a commonly prescribed drug is unlikely to work, or that a different dosage is required.

While this approach is gradually entering mainstream healthcare systems, adoption remains uneven. Private providers are often able to offer broader testing and faster integration into care, reinforcing the gap between those with access to personalised medicine and those without, while mass-market firms such as 23andMe offer relatively low-cost genetic testing.

At the more specialised end, companies such as Veritas Genetics and Human Longevity provide whole-genome sequencing alongside physician-led interpretation and ongoing health programmes for individuals.

For UHNWIs, the choice of provider often hinges not just on scientific capability, but on discretion. Genetic data is uniquely sensitive, and concerns about privacy, storage and potential misuse remain central to the decision-making process.

Despite falling sequencing costs, comprehensive genomic programmes remain expensive. Basic genetic tests can cost a few hundred US dollars, but full genome sequencing with clinical interpretation typically runs into the thousands. Ongoing programmes that include continuous monitoring and personalised care can cost significantly more.

This has created a two-tier system. While elements of genetic testing are becoming more accessible, the most advanced forms of personalised medicine remain largely confined to those able to pay for private care.

Even for those with the resources, for all its promise, personalised medicine is far from a crystal ball. Genetic testing can highlight risk factors, but it cannot fully account for environmental factors, lifestyle choices or the randomness inherent in biology. Nor can it predict exactly when, or if, a condition will develop.

For individuals like Carole, the experience can be as much psychological as medical. “Because nothing alarming came up, I think I’ve ended up just trusting my genes to carry me through,” she says. “I mean that’s probably a case of famous last words, but it has given me a degree of reassurance.”