Leveraging Genomic Associations in Precision Digital Care for Weight Loss: Cohort Study

Sinha, Rajeev; Kachru, Dashyanng; Ricchetti, Roshni Ray; Singh-Rambiritch, Simitha; Muthukumar, Karthik; Singaravel, Vidhya; Irudayanathan, Carmel; Reddy-Sinha, Chandana; Junaid, Imran; Sharma, Garima; Francis-Lyon, Patricia

doi:10.2196/25401

Cited by 9 publications

(8 citation statements)

References 116 publications

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“…Digbi Health has implemented a personalized digital care intervention that uses its multi-omics platform to provide dietary and lifestyle recommendations personalized using genetic and microbiome information. The intervention has been shown to deliver body weight loss in over 70% of individuals [ 31 ], reduction of fasting blood glucose level by 17.55% and an average reduction of HbA1c level by 6.27% [ 32 ], and a significant reduction in the symptomatology of functional gastro-intestinal disorders (FGIDs) [ 33 ]. This study addresses if gut microbiome taxa or functions and genetic markers explain body weight loss’s effect on mental health.…”

Section: Introductionmentioning

confidence: 99%

Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures

Pedroso¹,

Kumbhare²,

Joshi³

et al. 2022

JPM

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Neuropsychiatric diseases and obesity are major components of morbidity and health care costs, with genetic, lifestyle, and gut microbiome factors linked to their etiology. Dietary and weight-loss interventions can help improve mental health, but there is conflicting evidence regarding their efficacy; and moreover, there is substantial interindividual heterogeneity that needs to be understood. We aimed to identify genetic and gut microbiome factors that explain interindividual differences in mental health improvement after a dietary and lifestyle intervention for weight loss. We recruited 369 individuals participating in Digbi Health’s personalized digital therapeutics care program and evaluated the association of 23 genetic scores, the abundance of 178 gut microbial genera, and 42 bacterial pathways with mental health. We studied the presence/absence of anxiety or depression, or sleep problems at baseline and improvement on anxiety, depression, and insomnia after losing at least 2% body weight. Participants lost on average 5.4% body weight and >95% reported improving mental health symptom intensity. There were statistically significant correlations between: (a) genetic scores with anxiety or depression at baseline, gut microbial functions with sleep problems at baseline, and (b) genetic scores and gut microbial taxa and functions with anxiety, depression, and insomnia improvement. Our results are concordant with previous findings, including the association between anxiety or depression at baseline with genetic scores for alcohol use disorder and major depressive disorder. As well, our results uncovered new associations in line with previous epidemiological literature. As evident from previous literature, we also observed associations of gut microbial signatures with mental health including short-chain fatty acids and bacterial neurotoxic metabolites specifically with depression. Our results also show that microbiome and genetic factors explain self-reported mental health status and improvement better than demographic variables independently. The genetic and microbiome factors identified in this study provide the basis for designing and personalizing dietary interventions to improve mental health.

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Section: Introductionmentioning

confidence: 99%

Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures

Pedroso¹,

Kumbhare²,

Joshi³

et al. 2022

JPM

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“…In this context, the evidence presented in this and our previous studies supports this premise. It highlights microbial taxa and their functions that may be targeted to improve the gut microbiome composition with concomitant positive effects in health outcomes, including obesity, cardiovascular health, mental health, and functional gastrointestinal disorders 23–26 .…”

Section: Discussionmentioning

confidence: 99%

“…Digbi Health has developed a digital therapeutics program based on the participants' multi-omic signals (genetics and gut microbiome), along with self-reported data and data from wearable devices. The outcomes of the weight loss program in different cohorts of individuals have been recently published, demonstrating its applicability not only in weight loss 23 , but also in reducing fasting blood glucose and HbA1c levels 24 , improving mental health symptoms 25, and functional gastrointestinal disorders 26 .…”

Section: Introductionmentioning

confidence: 99%

Longitudinal gut microbial signals are associated with weight loss: insights from a digital therapeutics program

Kumbhare¹,

Pedroso²,

Joshi³

et al. 2023

Preprint

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Obesity is a significant health problem due to its profound health deteriorating effects and high costs for healthcare systems. There exist lifestyle and pharmacological interventions available to prevent and reverse obesity; however, at the population level, these have shown to be insufficient, and we continue to see a worldwide increase in obesity prevalence. The gut microbiome has been shown to influence the susceptibility to weight gain and difficulty in losing weight and to be associated with successful long-term weight loss. Therefore, multiple studies have suggested that obesity interventions should consider the gut microbiome as a primary target through an improved diet and a crucial endpoint to monitor. However, there is a paucity of evidence regarding how to tailor the diet for an individual's microbiome and what changes are expected to occur due to successful weight management. Digital therapeutics solutions have emerged as an exciting alternative to increase population access, reduce costs, and have the potential to accompany individuals on their health-promoting journey closely. Digbi Health has developed a dietary and lifestyle program to achieve weight loss that effectively reduces weight and improves diverse health outcomes by prioritizing and personalizing food ingredients to match an individual's genetic profile and nurture the gut microbiome. In this study, we analyze the weight loss pattern and microbiome profile of 103 individuals to identify the effects of the weight loss program on the gut microbiome between their baseline and follow-up samples. We found that 80% of individuals lost weight during the study. Analysis of their gut microbiome identified genera, functional pathways, and microbial communities associated with BMI changes and dietary and lifestyle program. The microbial genera and functional pathways associated with a reduction in BMI during the study include several previously reported in the literature, including Akkermansia, Christensenella, Oscillospiraceae, Alistipes, and Sutterella, short-chain fatty acid (SCFA) production and degradation of simple sugars like arabinose, sucrose, and melibiose. Network analysis identified two microbiome communities associated with BMI, one of which also significantly responded to the weight loss program, which includes multiple known associations with BMI and obesity. Our findings provide additional evidence for using the gut microbiome as an endpoint of weight loss program and highlight how it positively impacts the gut microbiome, with significant parallels in weight loss and health outcomes. These results provide additional evidence for known microbiome biomarkers of obesity and highlight new ones that warrant further research.

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“…Overweight and obesity are known risk factors for the co-occurrence of functional gastrointestinal disorders (FGIDs), and obesity has been shown to negatively impact clinical outcomes of FGID treatment ( Emerenziani et al, 2019 ). Dietary interventions can produce significant weight loss on overweight and obese subjects ( Sinha et al, 2021 ), and at the same time can deliver reduction of FGID symptomatology ( Manning and Biesiekierski, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Digital Therapeutics Care Utilizing Genetic and Gut Microbiome Signals for the Management of Functional Gastrointestinal Disorders: Results From a Preliminary Retrospective Study

Kumbhare¹,

Francis-Lyon

Kachru

et al. 2022

Front. Microbiol.

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Diet and lifestyle-related illnesses including functional gastrointestinal disorders (FGIDs) and obesity are rapidly emerging health issues worldwide. Research has focused on addressing FGIDs via in-person cognitive-behavioral therapies, diet modulation and pharmaceutical intervention. Yet, there is paucity of research reporting on digital therapeutics care delivering weight loss and reduction of FGID symptom severity, and on modeling FGID status and symptom severity reduction including personalized genomic SNPs and gut microbiome signals. Our aim for this study was to assess how effective a digital therapeutics intervention personalized on genomic SNPs and gut microbiome signals was at reducing symptomatology of FGIDs on individuals that successfully lost body weight. We also aimed at modeling FGID status and FGID symptom severity reduction using demographics, genomic SNPs, and gut microbiome variables. This study sought to train a logistic regression model to differentiate the FGID status of subjects enrolled in a digital therapeutics care program using demographic, genetic, and baseline microbiome data. We also trained linear regression models to ascertain changes in FGID symptom severity of subjects at the time of achieving 5% or more of body weight loss compared to baseline. For this we utilized a cohort of 177 adults who reached 5% or more weight loss on the Digbi Health personalized digital care program, who were retrospectively surveyed about changes in symptom severity of their FGIDs and other comorbidities before and after the program. Gut microbiome taxa and demographics were the strongest predictors of FGID status. The digital therapeutics program implemented, reduced the summative severity of symptoms for 89.42% (93/104) of users who reported FGIDs. Reduction in summative FGID symptom severity and IBS symptom severity were best modeled by a mixture of genomic and microbiome predictors, whereas reduction in diarrhea and constipation symptom severity were best modeled by microbiome predictors only. This preliminary retrospective study generated diagnostic models for FGID status as well as therapeutic models for reduction of FGID symptom severity. Moreover, these therapeutic models generate testable hypotheses for associations of a number of biomarkers in the prognosis of FGIDs symptomatology.

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Leveraging Genomic Associations in Precision Digital Care for Weight Loss: Cohort Study

Cited by 9 publications

References 116 publications

Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures

Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures

Longitudinal gut microbial signals are associated with weight loss: insights from a digital therapeutics program

Digital Therapeutics Care Utilizing Genetic and Gut Microbiome Signals for the Management of Functional Gastrointestinal Disorders: Results From a Preliminary Retrospective Study

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