Medical genetics, as applied to rare diseases, has been characterized by the rapid application in the clinic of the transformative genomic technologies that drove initial research discoveries. There are now targeted genetic tests for nearly all clinical presentations attributable to large-impact alleles, alongside more extensive genome-sequencing assays that, when necessary, enable interrogation of a longer list of relevant genes. Genetic testing for symptomatic individuals and at-risk relatives occurs routinely in many medical specialties. In parallel, the use of somatic cancer testing has increased as therapies targeted to specific mutational events have entered clinical practice (these developments are reviewed elsewhere131,132).

For patients with symptoms that indicate a probable monogenic aetiology (such as retinal degeneration, hearing loss or cardiomyopathy), targeted panels are typically the platform of choice133, although they are increasingly performed on a more extensive sequence backbone. For more complex phenotypes—those without a clear match to a specific syndrome, such as neurodevelopmental disorders and multiple congenital anomalies—testing has gravitated towards early deployment of exome and genome-sequencing platforms that offer speedy resolution of what has historically often been a traumatic diagnostic odyssey15,134. The power of genomic diagnosis is especially clear for those presenting with monogenic neurodevelopmental disorders and critically ill infants135,136. Sequencing of the parent–offspring trio can detect de novo variation in dominant disorders and phase biallelic rare variants in recessive disease13.

The transition from targeted gene tests to genomic sequencing enables recursive reanalysis, including reinterpretation of individual sequences on the basis of subsequent discoveries regarding causal disease alleles and their phenotypic consequences137. However, improved molecular diagnostics are required to ensure reliable detection of a subset of genetic disorders, including those arising from triplet repeats and complex rearrangements138. Deep sequencing of affected tissues for mosaic variants and the use of RNA sequencing to detect noncoding variants that drive early-onset disease (for example, through effects on splicing) represent new fronts for clinical diagnostics30.

Other examples of the rapid adoption of new genomic technologies include noninvasive prenatal testing (more than ten million tests by 2018 across multiple countries139,140,141) and the use of recessive carrier panels for couples planning pregnancies. Newborn screening is now universal in many countries, although it is limited to disorders combining high-throughput low-cost detection with effective early interventions (such as diet restrictions or enzyme replacement)142. Genetic diagnostics are also increasingly applied to newborn screening as a reflex test following an abnormal (for example, metabolic) screening test143. Over the next decade, the repertoire of disorders captured by neonatal screening and prenatal testing is likely to expand markedly. Whereas prenatal testing may be more effective at avoiding disease, the associated ethical issues are more complex144.

Although genetic testing for rare disease and cancer has exploded, there has been more limited uptake of genetic information in other aspects of healthcare. For example, despite multiple examples of clinically important genetic markers related to drug efficacy and side-effect profile145, the roll-out of pharmacogenetics has been hampered by a range of factors, including lack of clinical decision support in electronic medical systems to guide the drug choice or dosing by the physician. This has been compounded by challenges in diagnostic testing: complex haplotype structures and structural variants at some key drug metabolism loci necessitate genome sequencing or specific targeted panels to detect all clinically relevant variants.

For common diseases, translational attention is currently focused on the clinical potential of polygenic risk scores. The development of robust polygenic scores for several common diseases has been catalysed by more precise per-variant effect estimates from larger GWAS datasets, improved algorithms for combining information across millions of single-nucleotide polymorphisms, and large-scale biobanks that support score validation69,146,147. For example, a genome-wide polygenic score for heart attack, incorporating 6.6 million variants, indicates that 5% of European-descent individuals have a risk of future cardiac events equivalent to that seen in those with less frequent monogenic forms of hypercholesterolaemia69. Increasingly, the shift from array-based genotyping to sequence-based analysis is facilitating risk prediction, which integrates information from rare, large-effect alleles with that from polygenic scores93. By improving the capture of genetic risk, particularly in non-European populations, and integrating environmental and biomarker data to quantify aspects of non-genetic risk, it should be possible to achieve increasingly accurate prediction of individual disease risk, and to use this information to tailor screening, prevention and treatment. Success will depend on developing models of risk that robustly integrate these diverse data types and on optimizing the strategies deployed to ensure effective implementation.

The absence of evidence-based guidelines to support healthcare recommendations continues to hinder the clinical applications of genetic data. In some countries, this is compounded by confusion over reimbursement and disparities in testing across society148. Many healthcare professionals lack experience in genomic medicine and need education and guidance to practice in the rapidly evolving space of genetic and genomic testing149. One consequence of these difficulties has been an expanding direct-to-consumer testing market, variably controlled by country-specific regulations150, which is moving beyond a focus on ancestry and personal traits, towards models in which individuals have direct access to ordering physicians and genetic counselors151. The risk of commercial influence in this model remains high. There are concerns about the consequences of unfettered release of genetic data of dubious or inflated clinical relevance, and limited infrastructure to pull these results into mainstream medical systems.

These advances have fostered debate about the value of genetics for population screening, for both monogenic and complex disorders. Population screening for monogenic disorders is most likely to be initiated for conditions for which risk estimates are well-understood and there are actionable interventions (for example, Lynch syndrome and familial hypercholesterolaemia). Expansion to other disorders requires better understanding of the penetrance of pathogenic alleles in unselected populations152 and caution before extending screening to longer lists of genes that are less securely implicated in disease causation153. As certain countries consider universal capture of genome-wide genetic data at birth or later in life, key questions concern the strategies for releasing this information to citizens and their medical teams to support individual healthcare.

Ultimately, barriers to genomic medicine are most directly overcome by demonstrating clinical utility in disease management and therapeutic decision-making, with evidence for improved patient outcomes. Hereditary cancers provide multiple examples, such as the use of BRCA1/BRCA2 testing to inform PARP inhibitor treatment in patients with cancer154. There is a growing list of diseases for which a molecular diagnosis results in specific interventions designed to improve patient outcomes (https://www.ncbi.nlm.nih.gov/books/NBK1116/) (some examples are listed in Table 1), and there are currently more than 50 FDA-approved drugs for genetic disorders155. Although gene therapy has been slow to evolve since its early introduction, recent advances in gene editing are reinvigorating approaches to treat disorders by manipulation of the underlying genetic defects156.