Overview

rs1367117 is a genetic variant on gene APOB associated with Familial hypercholesterolemia and Familial hypobetalipoproteinemia 1.

This variant is located on chromosome 2. The variations at position 21041028 are the genetic letters A/A, C/C, G/G, A/C, C/G, A/G

Since humans have each twice (one from each parent), these letter-variations occur on both chromosomes. People can have the same or different letters on both chromosomes. Every person's individual variation combination is referred to as genotype. For variant rs1367117 there are 6 currently known genotypes : A/A, C/C, G/G, A/C, C/G or A/G

Short Overview

Variant Location

rs1367117 is located on gene APOB in chromsome 2. Use the genome browser to explore the location of rs1367117 and its genetic neighbourhood.

Conditions & Traits

rs1367117 affects the following conditions and traits:

Pathogenicity

rs1367117 affects the following conditions:

Pharmacogenetics

rs1367117 affects the following drugs:

Genome Browser

This interactive browser visualizes what no human can see with the naked eye - our DNA. From a down to a specific position on a . The position you are looking at here is the exact location of variant rs on gene APOB. Explore more variants and their effects on the body by browsing left and right along the DNA strand.

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Did you know genetic variants affect drugs?

Mutations are changes in genes and genetic variations are differences in the DNA among people. Variants are tiny changes in just one piece of the DNA while haplotypes are groups of these changes that usually come together.

Dr. Wallerstorfer Dr. Wallerstorfer

Conditions & Traits of rs1367117

The different genotypes of variant rs1367117 can affect the likelyhood of developing certain traits or conditions. Current research shows that 2 conditions and 0 traits are associated with rs1367117. The following table shows the relationship between genotypes and conditions and traits.

Classification of Variants

Variants can be classified either based on scientific studies or clinical tests. Scientific studies classifications aim to uncover the function of genetic variants and their role in conditions, traits, and evolution. Variants are categorized according to their functional effect, such as loss-of-function (reduced gene activity), gain-of-function (increased gene activity), neutral (no significant impact) or evolutionary conservation. This classification uses experimental data, population studies, and computational analyses to understand the long-term effects of variants. Clinical testing classifications, however, focus on the immediate health impact on the human body, distinguishing five categories from disease causing (harmful) to no effect (not harmful). This classification relies on a mix of family history, lab tests, and computer predictions, aiming to assist doctors in making medical decisions.

Conditions

2

Genotype

A

A

Level of evidence

Sources

Likely no effect

Unisex

2 Sources

Participants: 0

The genotype with the letters A/A is thought to have no effect on your disease risk. This means that the scientific evidence is still somewhat unclear about its effect. Carriers of this genetic result are usually not at risk of developing the disease.

Genotype

G

G

Level of evidence

Sources

No effect

Unisex

2 Sources

Participants: 0

The genotype with the letters G/G is thought to have no effect on your disease risk. Carriers of this genetic result are usually not at risk of developing the disease.

Genotype

A

G

Level of evidence

Sources

Likely no effect

Unisex

2 Sources

Participants: 0

The genotype with the letters A/G is thought to have no effect on your disease risk. This means that the scientific evidence is still somewhat unclear about its effect. Carriers of this genetic result are usually not at risk of developing the disease.

Pharmacogenetics

The genetic variant rs1367117 impacts how certain medications work in the body. This difference may cause some of us to require different dosage amounts to achieve the desired effects, while others might experience more apparent side-effects. As a result, healthcare providers may need to adjust prescriptions for those individuals with rs1367117. Ultimately, understanding our genetic makeup helps improve the overall effectiveness and usability of medications. Tailoring treatments based on genetics ensures a safer, more personalized healthcare experience.

Genotype
Level of evidence
Impacts
Summary
AA

Breakdown

Drug Effect

Side Effects

Dosage

Individuals with the genotype A/A have decreased Drug Effect to IRBESARTAN.

more info

AG

Breakdown

Drug Effect

Side Effects

Dosage

Individuals with the genotype A/G have increased Drug Effect to IRBESARTAN.

more info

GG

Breakdown

Drug Effect

Side Effects

Dosage

Individuals with the genotype G/G have increased Drug Effect to IRBESARTAN.

more info

Legend:

Increased

Decreased

No known effect

Genotype
AA
Impacts

Breakdown

Drug Effect

Side Effects

Dosage

Summary

Individuals with the genotype A/A have decreased Drug Effect to IRBESARTAN.

Level of evidence

More info

Genotype
AG
Impacts

Breakdown

Drug Effect

Side Effects

Dosage

Summary

Individuals with the genotype A/G have increased Drug Effect to IRBESARTAN.

Level of evidence

More info

Genotype
GG
Impacts

Breakdown

Drug Effect

Side Effects

Dosage

Summary

Individuals with the genotype G/G have increased Drug Effect to IRBESARTAN.

Level of evidence

More info

Legend:

Increased

Decreased

No known effect

Drugs related to rs1367117

All drugs that are linked to rs1367117 are listed here.

Studies and Sources

All of the resources below examine variant rs1367117

Exploring genetic determinants of plasma total cholesterol levels and their predictive value in a longitudinal study. (3/7/11)

Yingchang Lu, Edith J M Feskens, Jolanda M A Boer, Sandra Imholz, W M Monique Verschuren, Cisca Wijmenga, Anika Vaarhorst, Eline Slagboom, Michael Müller, Martijn E T Dollé

PubMed: 20832063
Meta-analysis of lipid-traits in Hispanics identifies novel loci, population-specific effects, and tissue-specific enrichment of eQTLs. (1/19/16)

Jennifer E Below, Esteban J Parra, Eric R Gamazon, Jason Torres, S Krithika, Sophie Candille, Yingchang Lu, Ani Manichakul, Jesus Peralta-Romero, Qing Duan, Yun Li, Andrew P Morris, Omri Gottesman, Erwin Bottinger, Xin-Qun Wang, Kent D Taylor, Y-D Ida Chen, Jerome I Rotter, Stephen S Rich, Ruth J F Loos, Hua Tang, Nancy J Cox, Miguel Cruz, Craig L Hanis, Adan Valladares-Salgado

PubMed: 26780889
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