Tag: diabetes

Predicting diabetes risk

A new computer algorithm can predict in the early stages of pregnancy, or even before pregnancy has occurred, which women are at a high risk of gestational diabetes. (photo from Weizmann Institute)

A new computer algorithm can predict in the early stages of pregnancy, or even before pregnancy has occurred, which women are at a high risk of gestational diabetes, according to a study by researchers at the Weizmann Institute of Science.

The study, reported recently in Nature Medicine, analyzed data on nearly 600,000 pregnancies available from Israel’s largest health organization, Clalit Health Services.

“Our ultimate goal has been to help the health system take measures so as to prevent diabetes from occurring in pregnancy,” said senior author Prof. Eran Segal of the institute’s computer science and applied mathematics, and molecular cell biology departments.

Gestational diabetes is characterized by high blood sugar levels that develop during pregnancy in women who did not previously have diabetes. It occurs in three to nine percent of all pregnancies and is fraught with risks for both mother and baby. Typically, gestational diabetes is diagnosed between the 24th and 28th weeks of pregnancy, with the help of a glucose tolerance test in which the woman drinks a glucose solution and then undergoes a blood test to see how quickly the glucose is cleared from her blood.

In the new study, Segal and colleagues started out by applying a machine learning method to Clalit’s health records on some 450,000 pregnancies in women who gave birth between 2010 and 2017. Gestational diabetes had been diagnosed by glucose tolerance testing in about four percent of these pregnancies. After processing the dataset – made up of more than 2,000 parameters for each pregnancy, including the woman’s blood test results and her and her family’s medical histories – the scientists’ algorithm revealed that nine of the parameters were sufficient to accurately identify the women who were at a high risk of developing gestational diabetes. The nine parameters included the woman’s age, body mass index, family history of diabetes and results of her glucose tests during previous pregnancies (if any).

Next, to make sure that the nine parameters could indeed accurately predict the risk of gestational diabetes, the researchers applied them to Clalit’s health records on about 140,000 additional pregnancies that had not been part of the initial analysis. The results validated the study’s findings: the nine parameters helped accurately identify the women who ultimately developed gestational diabetes.

These findings suggest that, by having a woman answer just nine questions, it should be possible to tell in advance whether she is at a high risk of developing gestational diabetes. If this information is available early on – in the early stages of pregnancy or even before the woman has gotten pregnant – it might be possible to reduce her risk of diabetes through lifestyle measures such as exercise and diet. On the other hand, women identified by the questionnaire as being at a low risk of gestational diabetes may be spared the cost and inconvenience of the glucose testing. (Visit weizmann.ac.il/sites/gd-predictor to access the self-assessment questionnaire.)

In more general terms, this study has demonstrated the usefulness of large human-based datasets, specifically electronic health records, for deriving personalized disease predictions that can lead to preventive and therapeutic measures.

The work was led by graduate students Nitzan Shalom Artzi, Dr. Smadar Shilo and Hagai Rossman from Segal’s lab at the Weizmann Institute of Science, who collaborated with Prof. Eran Hadar, Dr. Shiri Barbash-Hazan, Prof. Avi Ben-Haroush and Prof. Arnon Wiznitzer of the Rabin Medical Centre in Petach Tikvah; and Prof. Ran D. Balicer and Dr. Becca Feldman of Clalit Health Services.

 

Health benefits from wine

Ben-Gurion University Prof. Iris Shai, principal investigator of the CArdiovaSCulAr Diabetes and Ethanol (CASCADE) trial. (photo by Dani Machlis/BGU)

 

A glass of red wine every night may help people with type 2 diabetes manage their cholesterol and cardiac health, according to new findings from a two-year randomized controlled trial (RCT) led by researchers at Ben-Gurion University of the Negev (BGU). Additionally, both red and white wine can improve sugar control, depending on alcohol metabolism genetic profiling.

In this first long-term alcohol study, recently published in Annals of Internal Medicine, the researchers aimed to assess the effects and safety of initiating moderate alcohol consumption in diabetics, and sought to determine whether the type of wine matters. People with diabetes are more susceptible to developing cardiovascular diseases than the general population and have lower levels of “good” cholesterol. Despite the enormous contribution of observational studies, clinical recommendations for moderate alcohol consumption remain controversial, particularly for people with diabetes, due to lack of long-term RCTs, which are the “holy grail” of evidence-based medicine.

“Red wine was found to be superior in improving overall metabolic profiles, mainly by modestly improving the lipid profile, by increasing good (HDL) cholesterol and apolipoprotein A1 (one of the major constituents of HDL cholesterol), while decreasing the ratio between total cholesterol and HDL cholesterol,” the researchers explained.

The researchers concluded that “initiating moderate wine intake, especially red wine, among well-controlled diabetics, as part of a healthy diet, is apparently safe, and modestly decreases cardio-metabolic risk. The differential genetic effects that were found may assist in identifying diabetic patients in whom moderate wine consumption may induce greater clinical benefit.”

The researchers also found that only the slow alcohol-metabolizers who drank wine achieved an improvement in blood sugar control, while fast alcohol-metabolizers (with much faster blood alcohol clearance) did not benefit from the ethanol’s glucose control effect. Approximately one in five participants was found to be a fast alcohol-metabolizer, identified through ADH enzyme genetic variants tests.

Wine of either type (red or white) did not effect change in blood pressure, liver function tests, adiposity or adverse events/symptoms. However, sleep quality was significantly improved in both wine groups, compared with the water control group. All comparisons were adjusted for changes in clinical, medical and drug therapy parameters occurring among patients during the years of the study.

The two-year CArdiovaSCulAr Diabetes and Ethanol (CASCADE) randomized controlled intervention trial was performed on 224 controlled diabetes patients (aged 45 to 75), who generally abstained from alcohol. They gradually initiated moderate wine consumption, as part of a healthy diet platform, and not before driving. The trial completed with an unprecedented adherence rate of 87% after two years.

According to BGU Prof. Iris Shai, principal investigator of the CASCADE trial, and a member of the department of public health in the faculty of health sciences, “The differences found between red and white wine were opposed to our original hypothesis that the beneficial effects of wine are mediated predominantly by the alcohol. Approximately 150 millilitres of the dry red or white wines tested contained about 17 grams ethanol and 120 kilocalories, but the red wine had sevenfold higher levels of total phenols and four- to 13-fold higher levels of the specific resveratrol group compounds than the white wine. The genetic interactions suggest that ethanol plays an important role in glucose metabolism, while red wine’s effects additionally involve non-alcoholic constituents. Yet, any clinical implication of the CASCADE findings should be taken with caution with careful medical follow-up.”

The study was performed in collaboration with Prof. Meir Stampfer from Harvard University and with colleagues from University of Leipzig, Germany, and Karolinska Institute, Sweden.

In the new study that followed the research group’s three-month alcohol pilot RCT findings (Shai I., et al, Diabetes Care, 2007), the patients were randomized into three equal groups according to whether they consumed a five-ounce serving (150 millilitre) of mineral water, white wine or red wine with dinner every night for two years. Wine and mineral water were provided free of charge for the purposes of the study. Compliance with alcohol intake was tightly monitored, with patients returning their empty wine bottles and receiving their new supplies. All groups followed a non-calorie-restricted Mediterranean diet (following the group’s previous two-year dietary RCT findings; Shai I., et al, New England Journal of Medicine, 2008). Adherence was monitored using several validated assessment tools.

During the study, subjects underwent an array of comprehensive medical tests, including continuous monitoring of changes in blood pressure, heart rate and blood glucose levels, and follow-up for the dynamic of atherosclerosis and fat by ultrasound and MRI tests.