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  • 1
    In: BMC Medicine, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2022-12)
    Abstract: Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. We sought to evaluate the clinical effects of a personalized postprandial-targeting (PPT) diet on glycemic control and metabolic health in individuals with newly diagnosed T2DM as compared to the commonly recommended Mediterranean-style (MED) diet. Methods We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention ( n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. Results In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, − 19.8 ± 16.3 mg/dl × h, p 〈 0.001), mean glucose (mean difference between diets, − 7.8 ± 5.5 mg/dl, p 〈 0.001), and daily time of glucose levels 〉  140 mg/dl (mean difference between diets, − 2.42 ± 1.7 h/day, p 〈 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, − 16.4 ± 37 μmol/dl, p 〈 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, − 0.39 ± 0.48%, p 〈 0.001), fasting glucose (− 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (− 49 ± 46 mg/dl, p 〈 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c 〈 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. Conclusion In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. Trial registration ClinicalTrials.gov number, NCT01892956
    Type of Medium: Online Resource
    ISSN: 1741-7015
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2131669-7
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  • 2
    In: Cell Metabolism, Elsevier BV, Vol. 35, No. 5 ( 2023-05), p. 758-769.e3
    Type of Medium: Online Resource
    ISSN: 1550-4131
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 2174469-5
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    Elsevier BV ; 2018
    In:  Current Opinion in Biotechnology Vol. 51 ( 2018-06), p. 57-63
    In: Current Opinion in Biotechnology, Elsevier BV, Vol. 51 ( 2018-06), p. 57-63
    Type of Medium: Online Resource
    ISSN: 0958-1669
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
    detail.hit.zdb_id: 2019676-3
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    American Diabetes Association ; 2020
    In:  Diabetes Vol. 69, No. Supplement_1 ( 2020-06-01)
    In: Diabetes, American Diabetes Association, Vol. 69, No. Supplement_1 ( 2020-06-01)
    Abstract: Prediabetes is a leading risk factor for the development of type 2 diabetes mellitus (T2DM) and its metabolic complications. Current practice for prevention of diabetes includes weight loss-targeting dietary and lifestyle modifications but has had limited success. Alternative approaches, such as dietary interventions that directly target blood glucose levels for prevention of T2DM, are not well established and have been much less studied. In particular, postprandial (post-meal) glucose responses (PPGR) are a major determinant of glycemic control, but dietary methods for controlling PPGRs are rare and show limited efficacy. We previously recruited a population-based cohort of 900 people in which we continuously tracked blood glucose and obtained clinical and gut microbiota measurements. Our data of ∼50,000 PPGRs revealed that different people have vastly different responses to the same meal. We devised a machine learning algorithm based on clinical and microbiome features that accurately predicted personalized PPGRs to any food combination. Here, we sought to evaluate the long-term clinical efficacy of a dietary intervention based on our algorithm in prediabetes, and test the hypothesis that a dietary treatment that targets meal PPGR can lead to long-term improvements in glycemic control and other metabolic outcomes, as compared to a standard Mediterranean-style diet. To this end, we conducted a 6-month randomized controlled diet intervention trial (RCT) followed by a 6-month post-intervention follow-up program, and randomly assigned 225 adults with prediabetes to receive a Mediterranean-style (Med) diet or a Personalized Postprandial-targeting (PPT) diet. At 6 months, mean daily time of glucose levels above 140 mg/dl changed by -29% and -65% in the Med diet and PPT diet, respectively (p=3.4x10-10). Mean HbA1c% levels changed by -0.08% and -0.16% in the Med diet and PPT diet, respectively (p=6.9x10-3). The favorable effects of the ’PPT diet’ on glycemic control persisted also at one year follow up. Disclosure O. Ben-Yacov: None. A. Godneva: None. E. Segal: Consultant; Self; DayTwo.
    Type of Medium: Online Resource
    ISSN: 0012-1797 , 1939-327X
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2020
    detail.hit.zdb_id: 1501252-9
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  • 5
    In: BMJ Open, BMJ, Vol. 10, No. 10 ( 2020-10), p. e037859-
    Abstract: Metformin and diets aimed at promoting healthy body weight are the first line in treating type 2 diabetes mellitus (T2DM). Clinical practice, backed by clinical trials, suggests that many individuals do not reach glycaemic targets using this approach alone. The primary aim of the Personalised Medicine in Pre-diabetes—Towards Preventing Diabetes in Individuals at Risk (PREDICT) Study is to test the efficacy of personalised diet as adjuvant to metformin in improving glycaemic control in individuals with dysglycaemia. Methods and analysis PREDICT is a two-arm, parallel group, single-masked randomised controlled trial in adults with pre-diabetes or early-stage T2DM (with glycated haemoglobin (HbA1c) up to 8.0% (64 mmol/mol)), not treated with glucose-lowering medication. PREDICT is conducted at the Clinical Research Facility at the Garvan Institute of Medical Research (Sydney). Enrolment of participants commenced in December 2018 and expected to complete in December 2021. Participants are commenced on metformin (Extended Release, titrated to a target dose of 1500 mg/day) and randomised with equal allocation to either (1) the Personalised Nutrition Project algorithm-based diet or (2) low-fat high-dietary fibre diet, designed to provide caloric restriction (75%) in individuals with body mass index 〉 25 kg/m 2 . Treatment duration is 6 months and participants visit the Clinical Research Facility five times over approximately 7 months. The primary outcome measure is HbA1c. The secondary outcomes are (1) time of interstitial glucose 〈 7.8 mmol/L and (2) glycaemic variability (continuous glucose monitoring), (3) body weight, (4) fat mass and (5) abdominal visceral fat volume (dual-energy X-ray absorptiometry), serum (6) low-density lipoprotein cholesterol (7) high-density lipoprotein cholesterol and (8) triglycerides concentrations, (9) blood pressure, and (10) liver fat (Fibroscan). Ethics and dissemination The study has been approved by the St Vincent’s Hospital Human Research Ethics Committee (File 17/080, Sydney, Australia) and the Weizmann Institutional Review Board (File 528-3, Rehovot, Israel). The findings will be published in peer-reviewed open access medical journals. Trial registration number NCT03558867 .
    Type of Medium: Online Resource
    ISSN: 2044-6055 , 2044-6055
    Language: English
    Publisher: BMJ
    Publication Date: 2020
    detail.hit.zdb_id: 2599832-8
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  • 6
    In: Science Immunology, American Association for the Advancement of Science (AAAS), Vol. 6, No. 61 ( 2021-07-29)
    Abstract: The spillover of animal coronaviruses (aCoVs) to humans has caused SARS, MERS, and COVID-19. Although antibody responses displaying cross-reactivity between SARS-CoV-2 and seasonal/common cold human coronaviruses (hCoVs) have been reported, potential cross-reactivity with aCoVs and the diagnostic implications are incompletely understood. Here, we probed for antibody binding against all 7 hCoVs and 49 aCoVs represented as 12,924 peptides within a phage-displayed antigen library. Antibody repertoires of 269 recovered patients with COVID-19 showed distinct changes compared with 260 unexposed prepandemic controls, not limited to binding of SARS-CoV-2 antigens but including binding to antigens from hCoVs and aCoVs with shared motifs to SARS-CoV-2. We isolated broadly reactive monoclonal antibodies from recovered patients with COVID-19 who bind a shared motif of SARS-CoV-2, hCoV-OC43, hCoV-HKU1, and several aCoVs, demonstrating that interspecies cross-reactivity can be mediated by a single immunoglobulin. Using antibody binding data against the entire CoV antigen library allowed accurate discrimination of recovered patients with COVID-19 from unexposed individuals by machine learning. Leaving out SARS-CoV-2 antigens and relying solely on antibody binding to other hCoVs and aCoVs achieved equally accurate detection of SARS-CoV-2 infection. The ability to detect SARS-CoV-2 infection without knowledge of its unique antigens solely from cross-reactive antibody responses against other hCoVs and aCoVs suggests a potential diagnostic strategy for the early stage of future pandemics. Creating regularly updated antigen libraries representing the animal coronavirome can provide the basis for a serological assay already poised to identify infected individuals after a future zoonotic transmission event.
    Type of Medium: Online Resource
    ISSN: 2470-9468
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2021
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  • 7
    In: JAMA Network Open, American Medical Association (AMA), Vol. 5, No. 9 ( 2022-09-28), p. e2233760-
    Abstract: Interindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss. Objective To compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity. Design, Setting, and Participants The Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A 1c level ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m 2 using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes. Interventions Participants were randomized to either a low-fat diet ( & amp;lt;25% of energy intake; standardized group) or a personalized diet that estimates PPGR to foods using a machine learning algorithm (personalized group). Participants in both groups received a total of 14 behavioral counseling sessions and self-monitored dietary intake. In addition, the participants in the personalized group received color-coded meal scores on estimated PPGR delivered via a mobile app. Main Outcomes and Measures The primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling. Results Of a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was −4.31% (95% CI, −5.37% to −3.24%) for the standardized group and −3.26% (95% CI, −4.25% to −2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, −0.40% to 2.50%] ; P  = .16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P  = .05). Conclusions and Relevance A personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure. Trial Registration ClinicalTrials.gov Identifier: NCT03336411
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2022
    detail.hit.zdb_id: 2931249-8
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  • 8
    In: Immunity, Inflammation and Disease, Wiley, Vol. 10, No. 3 ( 2022-03)
    Abstract: Atopic dermatitis (AD) is a remitting relapsing chronic eczematous pruritic disease. Several studies suggest that gut microbiota may influence AD by immune system regulation. Methods We performed the first in‐human efficacy and safety assessment of fecal microbiota transplantation (FMT) for AD adult patients. All patients received 2 placebo transplantations followed by 4 FMTs each 2 weeks apart. AD severity and fecal microbiome profile were evaluated by the Scoring Atopic Dermatitis Score (SCORAD), the weekly frequency of topical corticosteroids usage, and gut microbiota metagenomic analysis, at the study beginning, before every FMT, and 1–8 months after the last FMT. Results Nine patients completed the study protocol. There was no significant change in the SCORAD score following the two placebo transplants. The average SCORAD score significantly decreased from baseline at Weeks 4–12 (before and 2 weeks after 4 times of FMT) (59.2 ± 34.9%, Wilcoxon p  = .011), 50% and 75% decrease was achieved by 7 (77%) and 4 (44%) patients, respectively. At Week 18 (8 weeks after the last FMT) the average SCORAD score decreased from baseline at Week 4 (85.5 ± 8.4%, Wilcoxon p  = .018), 50% and 75% decrease was achieved by 7 (77%) and 6 (66.7%) patients respectively. Weekly topical corticosteroids usage was diminished during the study and follow‐up period as well. Two patients had a quick relapse and were switched to a different treatment. Two patients developed exacerbations alleviated after an additional fifth FMT. Metagenomic analysis of the fecal microbiota of patients and donors showed bacterial strains transmission from donors to patients. No adverse events were recorded during the study and follow‐up period. Conclusions FMT may be a safe and effective therapeutic intervention for AD patients, associated with transfer of specific microbial species from the donors to the patients. Further studies are required to reconfirm these results.
    Type of Medium: Online Resource
    ISSN: 2050-4527 , 2050-4527
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2740382-8
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  • 9
    In: Med, Elsevier BV, Vol. 2, No. 2 ( 2021-02), p. 196-208.e4
    Type of Medium: Online Resource
    ISSN: 2666-6340
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
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  • 10
    In: Nature Medicine, Springer Science and Business Media LLC, Vol. 28, No. 2 ( 2022-02), p. 295-302
    Type of Medium: Online Resource
    ISSN: 1078-8956 , 1546-170X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 1484517-9
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