9.3 Genomics and the Human Story

[Separate note 9-1] Personal genomic medicine

Personal genomic medicine uses an individual genome in diagnosis, treatment and prevention decisions
Genomic information can support susceptibility, drug response and diagnostic reasoning
Most complex diseases involve many genes and environmental factors, so a single variant rarely predicts them
A detected variant often has uncertain clinical meaning and needs an interpretation step
Genomic information also concerns relatives, so consent, confidentiality and counselling matter
A genomic result does not replace diagnosis but is integrated with other clinical information

Genome sequence, reference genome and annotation are different concepts
The sequence is the base order, the reference is a comparison standard and the annotation records gene positions and function
Annotation includes genes, transcripts, exon boundaries, regulatory elements and repeats
A linear reference makes comparison easy but does not capture structural variation between populations
A pangenome represents several assembled genomes as a graph and addresses that limit
Gene number changes with annotation release, so source and version must be stated
Alternative splicing makes the number of transcripts exceed the number of genes
Protein-coding exons are a small fraction of the genome and are not proportional to gene number

The genome divides into coding and non-coding sequence, with non-coding sequence in the majority
Non-coding sequence includes regulatory elements, repeats and structural features, much of it of unknown function
Variants include single nucleotide changes, insertions, deletions, copy number variants, structural variants and repeat expansions
Changes of the same size differ greatly in effect depending on position and reading frame
A haplotype is a combination of variants inherited together on one chromosome
Alleles are alternative sequence forms at a locus, and each individual carries two
In families, haplotype transmission is tracked to show that a variant segregates with the trait

Genome comparison infers migration, admixture and divergence between populations
Ancient DNA directly shows past genetic composition and its relation to present populations
Principal component analysis summarises population structure in two dimensions
Genetic ancestry and social race categories are different concepts
Race categories are social constructs while genomic variation is distributed continuously
Within-population diversity is often greater than between-population difference
Sample composition and the choice of reference populations affect interpretation

Monogenic disease is localised by tracking a large-effect variant within families
Complex disease involves many small-effect variants, so population-scale association is needed
A genome-wide association study compares allele frequencies between cases and controls
A Manhattan plot displays the position and strength of signals across chromosomes
Linkage disequilibrium makes a whole region appear associated, so the causal variant needs separate work
An odds ratio gives relative risk but not absolute risk
Example: an odds ratio of 1.5 against a baseline risk of 1 percent gives a small absolute increase
Polygenic risk scores combine many variants but transferability between populations and environmental factors limit interpretation
Association is not causation and needs functional and further epidemiological evidence

Variant interpretation uses the categories pathogenic, likely pathogenic, uncertain significance, likely benign and benign
Categories can be reclassified as evidence accumulates
Clinical decisions combine variant interpretation with family history, phenotype and counselling
Social use of genomic findings raises discrimination, privacy and equity concerns
Data sharing, consent and return of results require explicit principles
Next steps extend to pangenomes, single cells, multi-omics and clinical integration

References

**표 9.3-3**Composition of the human genome
Component	Approximate character	Caution in interpretation
Protein-coding exons	A small fraction of the genome	Not proportional to gene number
Non-coding sequence	Includes regulatory, repeat and structural elements	Much of it has no known function
Gene number	Varies with annotation release	State the source and version
Alternative splicing	Several transcripts from one gene	Transcript number differs from gene number
Pangenome	Includes structural variation across populations	Addresses limits of a single linear reference

**표 9.3-1**Classes of genomic variation
Variant class	Typical observation	Possible biological effect
Single nucleotide variant	Substitution of one base	Synonymous, missense or nonsense change; altered regulation
Insertion or deletion	Addition or loss of a few bases	Frameshift and change in protein length
Copy number variant	Difference in repeat number of a segment	Change in gene dosage
Structural variant	Inversion, translocation or large deletion	Fusion genes and separation of regulatory regions
Repeat expansion	Increase in the number of short repeats	Protein aggregation and altered expression

**표 9.3-2**Genomic methods and the limits of their conclusions
Method	Main answer	Limit of the conclusion
Genome-wide association study	Association signal at population level	Does not give causation or individual risk directly
Manhattan plot	Position and strength of signals along chromosomes	Linkage disequilibrium leaves the causal variant unresolved
Odds ratio	Relative size of risk	Does not give absolute risk
Polygenic risk score	Combined score across variants	Limited transferability between populations
Variant interpretation guidelines	Clinical significance category	Uncertainty remains and reclassification can occur