Genetic Risk Factors Found in Gestational Diabetes
By LabMedica International staff writers Posted on 26 Feb 2020 |
Image: Illumina microarrays are a robust system that allow investigators to find variants in simple nucleotide polymorphisms (SNPs). The microarrays are subsequently scanned in the iScan system (Photo courtesy of LABSERGEN LANGEBIO).
Gestational diabetes mellitus (GDM) is a common pregnancy complication affecting 6%–15% of pregnancies globally. Although the condition resolves after delivery in most cases, women with a history of GDM have a more than sevenfold increased risk of developing type 2 diabetes (T2D) compared with women with a normoglycemic pregnancy.
Individual single nucleotide polymorphisms (SNPs) and genetic risk scores (GRSs) capturing the cumulative risk conferred by these SNPs have been associated with T2D risk in the general population. However, as women with a history of GDM already have an elevated baseline genetic risk for T2D compared with the general population. The role genetic factors play in the development of T2D among women with a history of GDM may differ from that in the general population.
A team of scientists at the at the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Rockville, MD, USA) sought to gauge whether genetic risk scores could distinguish women with a history of gestational diabetes who develop T2D from those who do not. They applied this score to two population cohorts, one from the USA and one from Denmark, to find that women with high genetic risk scores were more likely to go on to develop T2D. Their findings also indicated that eating healthy could mitigate some of that risk.
Genotyping was performed using the TaqMan quantitative polymerase chain reaction (PCR) method (Applied Biosystems, Foster City, CA, USA) in 1,855 study participants from the USA and 603 from Denmark. In all, 112 candidate SNPs were selected based on previous genome- wide association studies (GWAS) of T2D. Genotyping was additionally performed using high- density SNP markers platforms, including, HumanHap, Infinium, OncoArray or Infinium HumanCoreExome (Illumina, San Diego, CA, USA).
Based on recent genome-wide association studies in European populations, the scientists identified 59 SNPs associated with T2D risk that they bundled into a genetic risk score for the condition. They then genotyped 2,434 white women with a history of gestational diabetes from the US Nurses' Health Study II and the Danish National Birth Cohort and determined their genetic risk scores. Of the women in the study, 601 developed T2D during the median follow-up period of 21 years for the US cohort and 13 years for the Danish cohort.
A high genetic risk score was associated with increased risk of developing T2D in both the US and Danish cohorts. When broken up by quartiles, the highest-scoring group was 19% more likely to develop T2D than the lowest scoring group. Every five risk alleles were associated with a 7% increase in T2D risk in the US cohort and 9% increase in risk in the Danish cohort.
The authors concluded that in a study based on two independent populations with a long follow- up period, they observed a significant association of genetic risk factors with the development of T2D. The magnitude of association, however, was modest. The study was published on February 13, 2020 in the journal BMJ Open Diabetes Research & Care.
Related Links:
Eunice Kennedy Shriver National Institute of Child Health and Human Development
Applied Biosystems
Illumina
Individual single nucleotide polymorphisms (SNPs) and genetic risk scores (GRSs) capturing the cumulative risk conferred by these SNPs have been associated with T2D risk in the general population. However, as women with a history of GDM already have an elevated baseline genetic risk for T2D compared with the general population. The role genetic factors play in the development of T2D among women with a history of GDM may differ from that in the general population.
A team of scientists at the at the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Rockville, MD, USA) sought to gauge whether genetic risk scores could distinguish women with a history of gestational diabetes who develop T2D from those who do not. They applied this score to two population cohorts, one from the USA and one from Denmark, to find that women with high genetic risk scores were more likely to go on to develop T2D. Their findings also indicated that eating healthy could mitigate some of that risk.
Genotyping was performed using the TaqMan quantitative polymerase chain reaction (PCR) method (Applied Biosystems, Foster City, CA, USA) in 1,855 study participants from the USA and 603 from Denmark. In all, 112 candidate SNPs were selected based on previous genome- wide association studies (GWAS) of T2D. Genotyping was additionally performed using high- density SNP markers platforms, including, HumanHap, Infinium, OncoArray or Infinium HumanCoreExome (Illumina, San Diego, CA, USA).
Based on recent genome-wide association studies in European populations, the scientists identified 59 SNPs associated with T2D risk that they bundled into a genetic risk score for the condition. They then genotyped 2,434 white women with a history of gestational diabetes from the US Nurses' Health Study II and the Danish National Birth Cohort and determined their genetic risk scores. Of the women in the study, 601 developed T2D during the median follow-up period of 21 years for the US cohort and 13 years for the Danish cohort.
A high genetic risk score was associated with increased risk of developing T2D in both the US and Danish cohorts. When broken up by quartiles, the highest-scoring group was 19% more likely to develop T2D than the lowest scoring group. Every five risk alleles were associated with a 7% increase in T2D risk in the US cohort and 9% increase in risk in the Danish cohort.
The authors concluded that in a study based on two independent populations with a long follow- up period, they observed a significant association of genetic risk factors with the development of T2D. The magnitude of association, however, was modest. The study was published on February 13, 2020 in the journal BMJ Open Diabetes Research & Care.
Related Links:
Eunice Kennedy Shriver National Institute of Child Health and Human Development
Applied Biosystems
Illumina
Latest Clinical Chem. News
- 3D Printed Point-Of-Care Mass Spectrometer Outperforms State-Of-The-Art Models
- POC Biomedical Test Spins Water Droplet Using Sound Waves for Cancer Detection
- Highly Reliable Cell-Based Assay Enables Accurate Diagnosis of Endocrine Diseases
- New Blood Testing Method Detects Potent Opioids in Under Three Minutes
- Wireless Hepatitis B Test Kit Completes Screening and Data Collection in One Step
- Pain-Free, Low-Cost, Sensitive, Radiation-Free Device Detects Breast Cancer in Urine
- Spit Test Detects Breast Cancer in Five Seconds
- Electrochemical Sensors with Next-Generation Coating Advances Precision Diagnostics at POC
- First-Of-Its-Kind Handheld Device Accurately Detects Fentanyl in Urine within Seconds
- New Fluorescent Sensor Array Lights up Alzheimer’s-Related Proteins for Earlier Detection
- Automated Mass Spectrometry-Based Clinical Analyzer Could Transform Lab Testing
- Highly Sensitive pH Sensor to Aid Detection of Cancers and Vector-Borne Viruses
- Non-Invasive Sensor Monitors Changes in Saliva Compositions to Rapidly Diagnose Diabetes
- Breakthrough Immunoassays to Aid in Risk Assessment of Preeclampsia
- Urine Test for Monitoring Changes in Kidney Health Markers Can Predict New-Onset Heart Failure
- AACC Releases Comprehensive Diabetes Testing Guidelines