KSR2, variants, traits, and what the research shows

KSR2 - what this gene does

Variants in KSR2, a human gene, appear in genomic association databases across trait themes spanning rare disease, cancer, metabolic conditions, and nutrition. The breadth of trait themes across 149 catalogued variants suggests diverse biological involvement, though specific mechanisms are not characterised in the available summary data.

Key takeaways

• The two highest-magnitude signals in this gene are both flagged under rare disease.
• A cluster of magnitude-4.5 variants spans cancer, metabolic, and nutrition trait themes.
• Rare disease is the most recurrent trait theme, appearing across six independent variants.
• 149 variants are currently catalogued for this gene, indicating broad genomic coverage.
• These are population-level associations and do not predict outcomes for any individual.

Notable variants

The strongest signals come from rs2542037480 and rs2542061584, both at magnitude 5.0 and both associated with rare disease. Among the magnitude-4.5 cluster, rs112647489 is linked to cancer, rs816189 to metabolic traits, and rs61937726 to nutrition. Several additional magnitude-4.5 variants - rs10161304, rs10431397, rs2393334, rs642846, and rs77551001 - have database entries but detailed trait annotations are not available in the current summary data.

Trait associations

Rare disease is the most heavily represented trait theme, with independent signals from rs2542037480, rs2542061584, rs1010452610, rs1173089162, rs1242975583, and rs1271054017 - recurrence across multiple independent variants in the same gene strengthens the association signal within this theme. Cancer appears as a trait theme for rs112647489, metabolic conditions for rs816189, and nutrition for rs61937726.

Evidence quality

The two magnitude-5.0 rare disease variants represent the strongest signals in this dataset. The three variants with published pages - rs10161304, rs10431397, and rs112647489 - were not accompanied by editorial summaries in this input, limiting interpretability. Effect sizes, odds ratios, and sample sizes are absent from the available data, preventing a full assessment of clinical relevance. These signals are consistent with GWAS (genome-wide association study - a type of study that scans many people's genomes for variants statistically associated with a trait) methodology; the absence of replication data across independent cohorts is an important caveat.

What this is NOT

These variants are population-level statistical signals, not deterministic predictors of disease or any trait for any individual. Nothing here constitutes medical advice, a diagnosis, or a recommendation to take any action.