Technological readiness and implementation of genomic-driven precision medicine for complex diseases

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data

Associations between Attention-Deficit/Hyperactivity Disorder and various eating disorders: A Swedish nationwide population study using multiple genetically informative approaches

Background Although attention-deficit hyperactivity/impulsivity disorder (ADHD) and eating disorders (EDs) frequently co-occur, little is known about the shared etiology. In this study we comprehensively investigated the genetic association between ADHD and various EDs, including anorexia nervosa (AN) and other EDs (OED, including bulimia nervosa [BN]). Methods We applied different genetically informative designs to register-based information of a Swedish nationwide population (N=3,550,118). We first examined the familial co-aggregation of clinically diagnosed ADHD and EDs across multiple types of relatives. We then applied quantitative genetic modeling in full-sisters and maternal half-sisters to estimate the genetic correlations between ADHD and EDs. We further tested the associations between ADHD polygenic risk scores (PRS) and ED symptoms, and between AN PRS and ADHD symptoms, in a genotyped population-based sample (N=13,472). Results Increased risk of all types of EDs was found in individuals with ADHD (any ED: OR [95% CI]=3.97 [3.81-4.14], AN: 2.68 [2.15-2.86], OED: 4.66 [4.47-4.87], BN: 5.01 [4.63-5.41]) and their relatives compared to individuals without ADHD and their relatives. The magnitude of the associations reduced as the degree of relatedness decreased, suggesting shared familial liability between ADHD and EDs. Quantitative genetic models revealed stronger genetic correlation of ADHD with OED (0.37 [0.31-0.42]) than with AN (0.14 [0.05-0.22]). ADHD PRS correlated positively with ED symptom measures overall and sub-scales “drive for thinness” and “body dissatisfaction”, despite small effect sizes. Conclusions We observed stronger genetic association with ADHD for non-AN EDs than AN, highlighting specific genetic correlation beyond a general genetic factor across psychiatric disorders

Technological readiness and implementation of genomic-driven precision medicine for complex diseases

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment – genomic-driven precision medicine (GDPM) – may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data