Normal Variation & Patterns of Genetic Inheritance – Comprehensive Bullet-Point Notes

Outcomes

• Part 1 – Normal Variation
• Appreciate that genetic variation exists between individuals & populations.
• Describe structural and sequence-level forms of normal genetic variation.
• Part 2 – Patterns of Inheritance
• Recognise classic monogenic inheritance patterns & molecular mechanisms influencing them.
• Define multifactorial (polygenic + environmental) disease.

Genetic Variation – General Concepts

• Human genome diversity arises from differences in DNA sequence and/or chromosome structure.
• Variation occurs:
• Inter-individual (between people of the same population).
• Inter-population (between geographic / ethnic groups).
• Mechanisms generating diversity: meiotic recombination, DNA-replication mistakes, DNA-repair infidelity, random genetic drift, natural selection, migration.

Categories of Variation

• Structural (kilobase–megabase scale)
• Copy-Number: deletions / duplications.
• Positional: insertions, translocations.
• Orientational: inversions.
• Sequence-level (≤ few bp)
• Single-nucleotide substitutions.
• Small indels (insertions / deletions).
• Repetitive-sequence polymorphisms (tandem or interspersed; can be sub-microscopic or cytogenetically visible).
• Sharp et al. 2006: spectrum spans benign → pathogenic; repeats often benign but predispose to rearrangements / expansion-contraction disorders.

Molecular Causes of Variation

• DNA repair pathways combat exogenous & endogenous damage:
• Direct repair, mismatch repair, nucleotide/base excision.
• Double-strand break repair: homologous recombination (HR) & non-homologous end-joining (NHEJ).
• Replication errors: proof-reading failures, fork-stalling / template switching.
• Meiotic homologous recombination:
• Allelic HR (between alleles) – normal crossing-over.
• Non-allelic HR – can generate copy-number changes.
• Retrotransposition (LINEs, SINEs, retroviral elements) inserts cDNA copies via an RNA intermediate.

The Reference Human Genome

• Curated by Genome Reference Consortium; current build \text{GRCh38/hg38}.
• Clinical pipeline:

1. Detect deviation from reference.

2. Determine clinical significance of each variant.
   • UCSC Genome Browser used for visualisation.

Databases for Variant Interpretation

• Population frequency catalogues:
• gnomAD (sequence + structural variants).
• Database of Genomic Variants (DGV) – CNVs.
• Disease / gene-specific: CFTR2, etc.
• DECIPHER – pathogenic/likely-pathogenic CNVs, phenotype links.
• ClinVar – public archive of variant → phenotype assertions; includes benign through pathogenic, with evidence tiers.
• Levels of curation vary; always examine primary evidence.

ACMG/AMP Sequence-Variant Classification (Richards et al 2015)

• 5-tier system: 1 Benign, 2 Likely Benign, 3 VUS (Uncertain), 4 Likely Pathogenic, 5 Pathogenic.
• Evidence categories & strength:
• Population data: high MAF supports benign; absence supports pathogenic.
• Computational/predictive: multiple algorithms.
• Functional studies: well-established assays.
• Segregation, de novo status, allelic data, case-control enrichment, reputable clinical labs.
• Decision matrix (simplified):
• Benign: \text{MAF} > 5\% OR \ge 2 Strong benign criteria.
• Pathogenic: combinations such as 1\,\text{Very Strong} + 1\,\text{Strong} up to \text{≥ 2 Strong}, etc.
• Typically > 1 piece of congruent evidence required.

Case Study – SCN1A c.3637C>T (p.Arg1213*)

• 3-year-old girl, intractable epilepsy; gene panel found heterozygous nonsense variant.
• Evidence:
• Absent in gnomAD (population criterion PM2).
• ClinVar: multiple “Pathogenic” submissions without conflict (PP5).
• Nonsense → predicted loss-of-function in gene with known LOF mechanism (PVS1 = Very Strong).
• Identified de novo in unrelated patients with Dravet syndrome (PS2 / PS4).
• Classification: \text{Class 5 (Pathogenic)}.

CNV Interpretation (ACMG 2020 Technical Standard)

• Parallel 5-tier schema for constitutional copy-number variants.
• Evidence categories: size, gene content, dosage sensitivity, inheritance, patient phenotype concordance, population frequency.
• Example: 240 kb gain at 6q27 in boy with VSD & dysmorphism; no OMIM genes, overlaps common gains in DGV → likely benign / VUS.

Phenotypic Consequences of Variation

• Every individual harbours tens-of-thousands of germline variants.
• Possible outcomes:
• Neutral (no phenotype).
• Trait/disease susceptibility.
• Altered drug metabolism (pharmacogenomics).
• Highly penetrant disease (germline).
• Somatic driver mutations in tumours.

Patterns of Inheritance (Monogenic)

General

• Majority reside on autosomes (chr 1–22); minority on sex chromosomes.
• Modes: Autosomal Dominant (AD), Autosomal Recessive (AR), X-Linked Dominant (XLD), X-Linked Recessive (XLR), Codominant, Mitochondrial.

Autosomal Recessive (AR)

• Affected offspring usually born to unaffected carrier parents.
• Both sexes equally affected / transmit.
• Often observed with consanguinity.
• Molecular rule: two pathogenic alleles (homozygous or compound het).
• Example: Cystic Fibrosis – 1/25 Caucasians are CFTR carriers.

Autosomal Dominant (AD)

• Affected individual generally has an affected parent.
• Either sex transmits; male→male possible.
• Single pathogenic allele sufficient.
• Example: Achondroplasia (FGFR3).

X-Linked Inheritance

• No male-to-male transmission (sons inherit Y from father).
• X-Linked Dominant (XLD):
• Females more common / milder (due to X-inactivation).
• Example: Rett syndrome (MECP2).
• X-Linked Recessive (XLR):
• Males affected, females carriers (± mild).
• Example: Haemophilia A (F8).

Codominant

• Both alleles fully expressed in heterozygote.
• Example: Sickle-cell genetics:
• Hb^{A}/Hb^{A} – normal.
• Hb^{A}/Hb^{S} – sickle-cell trait.
• Hb^{S}/Hb^{S} – sickle-cell disease.

Mitochondrial (mtDNA)

• Maternal transmission only (sperm mt destroyed).
• Either sex affected.
• Heteroplasmy (mutant : wild-type mtDNA ratio) drives variable expressivity & generational fluctuation.

Basic Recurrence Risk Concepts

• After identifying a variant, families ask “what is the chance it will recur?”
• Punnett-square logic with appropriate mode:
• AR carrier × carrier ⇒ 25\% affected risk per pregnancy, etc.
• mtDNA: theoretically up to 100\% of offspring of affected female, modulated by heteroplasmy.

Factors Complicating Mendelian Expectations

• Incomplete / variable penetrance.
• Variable expressivity.
• De novo pathogenic variants.
• Gonadal (germline) mosaicism.
• Skewed X-inactivation.
• Multifactorial inheritance (polygenic + environment).

Penetrance (P) & Expressivity

• P = \dfrac{\text{individuals with disease}}{\text{individuals carrying pathogenic allele}}.
• Complete (100 %) vs reduced.
• Example full penetrance: HTT CAG repeat \ge 40.
• BRCA1 AD cancer – reduced penetrance (not all carriers develop cancer).
• Expressivity: severity / specific features differing among affected.
• Example: Marfan syndrome variability.

De Novo Variants

• Pathogenic allele arises in gamete or early embryo.
• In AD disease, explains isolated case with unaffected parents.
• In AR, one de novo plus one inherited allele occasionally seen.

Mosaicism

• Post-zygotic mutation → genetically distinct cell populations.
• Somatic mosaicism: phenotype restricted to tissues containing variant.
• Gonadal mosaicism: variant only in gametes → parent unaffected but recurrence risk > 0.
• 15!–!20\% of “new” pathogenic variants may in fact be due to gonadal mosaicism (e.g. Duchenne Muscular Dystrophy).

Skewed X-Chromosome Inactivation

• Normal Lyonisation random \sim50\%; skewing (> 80 : 20) causes carrier females to manifest XLR disease.
• Example: DMD manifesting carriers with muscle weakness.

Multifactorial / Polygenic Disease (Definition)

• Trait/disease results from cumulative effect of many common variants of small effect plus environmental influences.
• No simple Mendelian ratio; risk best estimated empirically (family recurrence data, polygenic risk scores).

Key Equations & Numerical References

• Penetrance formula (above).
• ACMG frequency cut-off for benign: \text{MAF} > 5\%.
• CF carrier frequency in Caucasians: 1/25.
• Gonadal mosaicism contributes 15\% – 20\% of apparently de novo variants.

Ethical / Practical Considerations

• Variant classification influences clinical decisions (screening, treatment, reproductive planning).
• Public databases (ClinVar, gnomAD) rely on data-sharing; misclassification risks patient harm.
• Penetrance uncertainty complicates counselling; shared decision-making essential.
• Equity: population databases under-represent some ancestries, affecting interpretive power.
• Disclosure of incidental findings (ACMG SF v3 list) raises autonomy vs beneficence debates.

Quick Reference – Study Checklist

• Know structural vs sequence variants & mechanisms creating them.
• Recall key databases (gnomAD, DGV, ClinVar, DECIPHER).
• Apply ACMG evidence categories to classify variants.
• Distinguish AD, AR, XLD, XLR, Codominant, Mitochondrial pedigrees.
• Explain penetrance, expressivity, de novo, mosaicism, skewed XCI.
• Calculate recurrence risks for standard crosses.
• Recognise examples: CFTR/CF (AR), FGFR3/Achondroplasia (AD), MECP2/Rett (XLD), F8/Haemophilia A (XLR), HBB/Sickle-cell (codominant), mtDNA/Leber Optic Neuropathy (mitochondrial).