Genetic Panel for Diabetes
DIABETESNOW has a large database of previously tested patients to ensure highly validated, accurate, and informative result interpretation.
DIABETESNOW Gene Panel
DIABETESNOW is a unique comprehensive genetic panel which tests for 16 genes associated with MODY, syndromic, neonatal, and mitochondrial causes of monogenic diabetes, in addition to pan-ancestry type 1 & 2 diabetes polygenic risk scores (PRS) and probability for type 1 diabetes (GenProb-T1D).
The 16 genes tested in our panel were carefully selected from a combination oxf research and clinical guidelines backed up by the Monogenic Diabetes Expert Panel (MDEP).1-3
The 16 genes tested in our panel were carefully selected from a combination oxf research and clinical guidelines backed up by the Monogenic Diabetes Expert Panel (MDEP).1-3
Monogenic diabetes is an inherited form of diabetes mellitus accounting for 1-2% of all cases. Classification of diabetes type is not always straightforward and misdiagnosis is common. Monogenic testing should be considered in individuals with diabetes diagnosed in the first 6 months of life, who lack typical features of type 1 or type 2 diabetes, mild stable hyperglycemia and diabetes, and hearing loss.3
Gene Name
MODY
Neonatal
Syndromic
Mitochondrial
ABCC8
APPL1
CEL
GATA4
GCK
HNF1A
HNF1B
HNF4A
INS
KCNJ11
MT-TE m.14709T>C
MT-TL1 m.3243A>G
NEUROD1
PDX1
RFX6
WFS1
GenProb-T1D
GenProb-T1D is a probability measurement of susceptibility for type 1 diabetes derived from PRS of type 1 and type 2 diabetes.4,5 The higher the GenProb-T1D, the more likely the patient has type 1 diabetes versus type 2 based on their genetic risk.
A positive genetic test result can:
Aid in diagnosis
Provide a tool to help determine diagnosis
for people who present with atypical diabetes
for people who present with atypical diabetes
Assess risk for asymptomatic individuals with family history using genetic probability
Global Diversity Array (GDA)
The Illumina Global Diversity Array (GDA) is a state-of-the-art genomic tool designed to enhance the precision and inclusivity
of genetic testing. With its comprehensive genomic coverage, the GDA captures a wide range of genetic variants across diverse populations and in turn providing patients with a polygenic risk score for type 1 and type 2 diabetes, making it an invaluable genetic panel.
KEY BENEFITS OF GDA:
of genetic testing. With its comprehensive genomic coverage, the GDA captures a wide range of genetic variants across diverse populations and in turn providing patients with a polygenic risk score for type 1 and type 2 diabetes, making it an invaluable genetic panel.
KEY BENEFITS OF GDA:
-
Extensive Genomic Coverage
The GDA covers over 1.8 million genetic variants, including rare and common variants, ensuring comprehensive analysis. -
Inclusivity
Designed to represent genetic diversity, the GDA improves the relevance and accuracy of genetic testing for individuals from various ancestries. -
High Resolution
Offers high-resolution insights into complex genetic structures, enhancing the detection of clinically significant variants. -
Versatility
It is ideal for a broad range of applications, from research
to clinical diagnostics, ensuring reliable and robust results.
Most hereditary cancers
This COMPREHENSIVE GERMLINE PANEL analyzes 88 clinically-relevant genes that are associated with genetic disorders, including most hereditary cancers.
Prostate cancer
PROSTATENOW is a germline test for people with prostate cancer. This test can be used to predict prognosis among men with localized prostate cancer, predict therapeutic responses for advanced patients, and predict cancer risk among unaffected men.
Breast cancer
There is an increased likelihood of a BRCA1 or BRCA2 mutation in patients with certain personal and family history characteristics and various clinical criteria. BRCANOW is a Next-Gen Sequencing (NGS)-based assay using a state-of-the-art platform to detect whether or not a mutation is present.
Colorectal cancer
LYNCHNOW is a cost-effective, screening tool that rapidly detects mutations that cause Lynch syndrome.
We're here to guide you through the process.
DIABETESNOW™ includes genetic counseling to walk you through our process and test results, along with any lifestyle or treatment alternatives depending on your results.
References:
1.Criteria Specification Registry. (n.d.). https://cspec.genome.network/cspec/ui/svi/affiliation/50016
2. Billings LK, Shi Z, Resurreccion WK, Wang CH, Wei J, Pollin TI, Udler MS, Xu J. Statistical evidence for high-penetrance MODY-causing genes in a large population-based cohort. Endocrinol Diabetes Metab. 2022 Nov;5(6):e372
3. ADA Guidelines: American Diabetes Association Professional Practice Committee (2024). Introduction and Methodology: Standards of Care in Diabetes-2024. Diabetes care, 47(Supplement_1), S1–S4. https://doi.org/10.2337/dc24-SINT
4. Billings LK, Shi Z, Wei J, Rifkin AS, Zheng SL, Helfand BT, Ilbawi N, Dunnenberger HM, Hulick PJ, Qamar A, Xu J. Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes. J Clin Endocrinol Metab. 2023 Dec 21;109(1):107-113
5. Billings LK, Shi Z, Mulford AJ, Wei J, Tran H, Ashworth A, Zheng SL, Dunnenberger HM, Hulick PJ, Sanders AR, Xu J. Validation of GenProb[1]T1D and its clinical utility for differentiating types of diabetes in a biobank from a US healthcare system. J Diabetes Investig. 2024 Aug 22
1.Criteria Specification Registry. (n.d.). https://cspec.genome.network/cspec/ui/svi/affiliation/50016
2. Billings LK, Shi Z, Resurreccion WK, Wang CH, Wei J, Pollin TI, Udler MS, Xu J. Statistical evidence for high-penetrance MODY-causing genes in a large population-based cohort. Endocrinol Diabetes Metab. 2022 Nov;5(6):e372
3. ADA Guidelines: American Diabetes Association Professional Practice Committee (2024). Introduction and Methodology: Standards of Care in Diabetes-2024. Diabetes care, 47(Supplement_1), S1–S4. https://doi.org/10.2337/dc24-SINT
4. Billings LK, Shi Z, Wei J, Rifkin AS, Zheng SL, Helfand BT, Ilbawi N, Dunnenberger HM, Hulick PJ, Qamar A, Xu J. Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes. J Clin Endocrinol Metab. 2023 Dec 21;109(1):107-113
5. Billings LK, Shi Z, Mulford AJ, Wei J, Tran H, Ashworth A, Zheng SL, Dunnenberger HM, Hulick PJ, Sanders AR, Xu J. Validation of GenProb[1]T1D and its clinical utility for differentiating types of diabetes in a biobank from a US healthcare system. J Diabetes Investig. 2024 Aug 22