What is SCD1 – rs508384, rs2167444 and Why Does the Cardio Zoomer Test for It?

Lipid desaturase gene variants

SCD1 is the gene for stearoyl‑CoA desaturase, an enzyme that converts certain saturated fatty acids into monounsaturated fats used in membranes and triglycerides. The common variants rs508384 and rs2167444 are single‑letter genetic differences that can influence SCD1 expression or activity. Knowing these variants helps explain individual differences in lipid processing and metabolic patterns within the Cardio Zoomer profile.

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SCD1 – rs508384, rs2167444

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About SCD1 – rs508384, rs2167444

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About SCD1 – rs508384, rs2167444

Overview and History

SCD1 encodes stearoyl‑CoA desaturase 1, a membrane‑bound enzyme that introduces a single double bond into long‑chain saturated fatty acids, creating monounsaturated fatty acids such as palmitoleate and oleate. Biochemically, SCD1 activity affects membrane fluidity, triglyceride synthesis, and the balance of saturated versus monounsaturated lipid species. Variants like rs508384 and rs2167444 are common single‑nucleotide polymorphisms (SNPs) in or near the SCD1 gene. These SNPs have been studied in metabolic research for their associations with altered SCD1 expression or inferred activity, and with downstream changes in lipid composition and metabolic signaling. They are not diagnostic on their own but provide genetic context for metabolic and lipid biomarker patterns.

Interpreting Highs and Lows

Genetic alleles associated with higher inferred SCD1 expression or activity may correlate with a relative increase in monounsaturated fatty acids, altered triglyceride handling, and shifts in lipid species that show up on advanced lipid panels. These patterns can co‑occur with metabolic and inflammatory marker changes, depending on the individual. Alleles linked to lower inferred SCD1 expression or activity may be associated with a higher proportion of saturated fatty acids, different triglyceride dynamics, and related shifts in lipidomic signatures. Interpretation requires integration with circulating lipid measures, insulin/glucose markers, inflammatory indicators, and other Cardio Zoomer results to understand overall cardiometabolic context.

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Cardio Zoomer includes SCD1 variants to add a genetic lens on fatty‑acid desaturation and lipid handling. These variants help explain why a person’s lipid composition or metabolic markers may differ from expected patterns and guide clinicians in interpreting multi‑marker profiles for personalized risk mapping.

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SCD1 – rs508384, rs2167444 FAQs

What is SCD1 – rs508384, rs2167444 and why is it important?

These are common genetic variants in the SCD1 gene, which helps make monounsaturated fats from saturated fats. The specific alleles can influence how strongly the gene is expressed or how active the enzyme is. That information helps explain individual differences in lipid composition and metabolic responses measured elsewhere in the Cardio Zoomer panel.

What does it mean if my SCD1 – rs508384, rs2167444 levels are low?

When people carry alleles associated with lower inferred SCD1 expression or activity, it may be linked to a higher proportion of saturated fatty acids and altered triglyceride or lipid species profiles. On its own this is a pattern, not a diagnosis; its clinical meaning depends on other Cardio Zoomer markers like advanced lipids, glucose/insulin measures, and inflammation indicators.

What does it mean if my SCD1 – rs508384, rs2167444 levels are high?

Alleles tied to higher inferred SCD1 expression or activity can be associated with increased monounsaturated fatty acids and changes in lipid handling detectable on detailed lipid testing. Elevated inferred activity should be interpreted alongside other metabolic, inflammatory, and lipid markers to assess overall cardiometabolic patterns.

Why is this biomarker included in the Cardio Zoomer?

SCD1 variants provide genetic context for how an individual metabolizes fats and forms lipid species. Combined with advanced lipid, metabolic, and inflammatory markers, they help clinicians detect patterns, explain atypical results, and build a more personalized cardiometabolic profile.

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