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Approved Research

Estimating the diagnostic and monitoring value of body composition analysis for health risks associated with Type 2 Diabetes and Alzheimer's Disease

Principal Investigator: Mr Rohith Haridas
Approved Research ID: 82143
Approval date: March 25th 2022

Lay summary

There are primarily two types of fat in the human body - visible(subcutaneous) and invisible(visceral). The visible fat is the jiggly mass residing right under our skin which we can usually feel or see and accounts for almost 90% of all the fat present in the body. In the right amounts, visible fat is considered healthy and even helps prevent certain diseases but when in excess, it contributes to obesity and associated health risks. The invisible fat on the other hand, is a much more serious fat deposit present in between organs especially in the abdomen and can only be seen through a medical imaging scan. This fat is considered dangerous because it is a major contributor to a myriad of health conditions like diabetes, brain disorders(dementia, Alzheimer's), certain cancers(e.g. prostate, breast, pancreatic) and associated heart diseases.

We at PMX are already equipped with a body composition solution to quantify these fat depots and muscles from body MRI scans. Using the UK Biobank data, we intend to validate how the distributions of these fat deposits vary across prediabetic, diabetic and healthy individuals; and thereby derive normative ranges for effective monitoring and control of diabetes and associated health risks. Parallelly or after this study, we also intend to validate the relationship between fat in the head versus fat(both visible and invisible) in the abdomen for Alzheimer's spectrum disorders because prior research by us have hinted an association between head and abdominal adiposity. Because head MRI scans are more predominantly available than whole body or abdominal MRI, we hope to unearth an indirect relationship between head adiposity and the onset of this neurodegenerative disease. The whole project is expected to take 6-8 months to complete(including validation) post curation of the dataset.

The public impact of this project post successful completion is that we'll be able to assess where a person stands with respect to his risk to all the aforementioned health conditions based on the derived normative ranges from fat quantification. The significant relationship between head and abdominal adiposity, once established, can also help in estimating abdominal fat from head MRI scan, thereby enabling an indirect estimation of the subject's risk to develop Alzheimer's spectrum disorders. This also cuts down the time spent by a person in MRI machines by at least 30 minutes due to the lack of need to undergo an additional whole body or abdominal MRI scan.