RESEARCH

Type 1 diabetes in the Israeli population

Type 1 diabetes, also known as Juvenile diabetes, is a severe chronic autoimmune disease. It affects over 20 million people worldwide [1], its frequency is currently increasing at ~2% a year [2], it has severe and costly implications on the health of patients, and it shortens their life expectancy by twelve years on average [3].

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Family and twin studies indicate that type 1 diabetes is highly heritable. In fact, it has the strongest expected genetic background of all complex diseases in humans, with 88% heritability [4]. However, despite large Genome-Wide Association Studies (GWAS), the genetic variants that cause type 1 diabetes are still unknown.

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It is estimated that rare genetic variants with large effects may play a central role in the disease. Nevertheless, all of the 23 previous genome-wide studies of type 1 diabetes were performed on heterogeneous populations [5], severely limiting the statistical power to detect rare variants. Furthermore, all of these studies were conducted by genotyping common SNPs and not by whole-genome sequencing, which is required to identify rare variants [1,6].

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In the Zeevi lab, we are currently initiating two large genetic studies of type 1 diabetes. Both studies share the same principle. We recruited Especially large nuclear families with at least two affected first-degree relatives and their healthy family members as controls. All of our participants are from genetically homogenous populations from around Israel, such as Ashkenazi Jews, Druze, Palestinians from the Jerusalem metropolitan area, and others.

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For these studies, we collaborate with leading endocrinologists from all around Israel (Hadassah, Shaare Tzedek, Schneider, Ziv, and Rambam medical centers). We apply cutting-edge sequencing technologies to gain high coverage and phased whole-genome. We then utilize advanced statistical and bioinformatic methods for genetic analysis of complex traits in families and founder populations.

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Our goal is to map genetic variants that have large effects on the risk of type 1 diabetes, variants that are rare globally but are common in specific Israeli populations. We will then use this information to design a custom genotyping array for estimating type 1 diabetes risk in Israeli populations. This array will be used in diabetes clinics, and provide true personalized medicine. Each patient or healthy but genetically high-risk individual can be monitored and treated according to his specific genetic variants.

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Type 1 diabetes in the UK population

The UK Biobank is a very large biomedical database with health and genomic information of 500,000 individuals from the UK, including thousands of type 1 diabetes patients. The UK Biobank recently released (Oct 29, 2021) the exome sequencing data of 450,000 participants, and is intending to release the full genomes of the participants in the near future.
We are currently initiating a study of type 1 diabetes in the UK Biobank database. 
We will use the exome sequencing, and later the full genomes, to identify novel and rare variants that are associated with the risk of developing type 1 diabetes. We will validate in the UK Biobank genetic variants that were identified in other cohorts, and we will develop and improve methods for calculating a genetic risk score for type 1 diabetes from genomic data.

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The genetic basis of height

Along with type 1 diabetes research, we also study the genetic basis of another complex trait – height.
In this research, we conduct bioinformatic analysis on data that was collected by Dr. Zeevi during his postdoc. These data include genotypes and heights of siblings from very large nuclear families (average of 12 and up to 20 siblings per nuclear family). We are using these data for developing tools to include the genotype of a child to predict his final height. This is important since only mid-parental height and bone age assessments are used today in the clinic to predict a child’s growth potential. By adding a genetic score to the growth assessment, one can achieve a more accurate estimation of the child’s growth potential, and thus improve the detection of deviations from the child’s expected growth.
This introduction of height genetic scores to the clinic may enable doctors to improve the diagnosis of various growth problems, and make more informed decisions on the need for growth hormone treatment in children.

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Our work is funded by the Israeli Science Fund (ISF), the Juvenile Diabetes Research Foundation (JDRF), and the Russell Berrie Foundation through the SPHERE diabetes program.