For many of us, I suspect that the words lipidomics and lipidome are new - they are to my spelling checker!
This is a very substantial paper with lots and lots of detail.
Things like the possibility of high density lipoprotein (HDL of cholesterol fame) going up or down or remaining unaltered in hypothyroidism are critical to any interpretation of blood lipid tests. Yet I suggest the majority are looked at with all the critical facilities required to read Janet and John.
I am a huge fan of the approach of measuring everything you can - then interpreting the individual results in the context of all the other results.
If you do a TSH test, the implicit assumption is either that they do have a thyroid issue (and this will show as high or low TSH), or they do not (in which case it will be "normal"). But the decision to do that TSH test is a sort of prejudgement. Whereas, if you measure everything, you might identify other causes of the symptoms reported.
Application of Human Plasma Targeted Lipidomics and Analysis of Toxic Elements to Capture the Metabolic Complexities of Hypothyroidism
5. Conclusions
Our study makes a significant contribution to deciphering the plasma lipidome precisely in people with hypothyroidism, as these are the patients who will potentially develop different manifestations of lipid disorders. A significant association between altered levels of several components of the plasma lipidome and several toxic trace elements with hypothyroidism was found. A set of 23 chemical substances have been identified that are fundamental in differentiating between healthy individuals and patients suffering from hypothyroidism. These include Al, Cd, Ni, As, and Pb, along with a large set of lipid compounds. We also identified a set of 17 different compounds and elements that were significantly different in patients depending on the type of disease: autoimmune or non-autoimmune hypothyroidism.
For several reasons, in-depth knowledge of the lipid profile of patients with hypothyroidism can be important. First, it is important for developing personalized treatment strategies that can effectively address each patient’s unique needs, thereby improving overall management and outcomes in treating patients. Hypothyroidism has a significant impact on metabolic rate, which can lead to profound changes in energy expenditure and nutrient utilization. Slow metabolism in HT patients can result in rapid weight gain. Understanding the specific metabolic changes associated with hypothyroidism can help tailor dietary treatments more effectively. Second, knowledge of the lipidome profile can provide information about risk factors and potential complications associated with HT. In particular, it is well known that altered lipid metabolism can increase the risk of cardiovascular diseases, which are a common comorbidity in HT patients. Profiling metabolic changes makes it possible to pre-emptively address these risks with appropriate interventions. Finally, metabolic profiling can also be a tool to monitor treatment effectiveness. Changes in specific metabolites can help assess the organism’s response to thyroid hormone replacement therapy or other treatments, allowing for timely adjustments in management strategies.
This work also highlights the great scientific potential of modern analytical techniques such as FIA-ESI-MS/MS and ICP-MS, capable of quickly generating a huge amount of data about a biological sample, as well as the application of novel statistical approaches in the analysis of bioanalytical and clinical data. In fact, when dealing with large datasets, it is crucial to choose the appropriate statistical analysis tools to extract the most information from them. The approach we used, based on MCFS-ID, has proven to be a powerful tool for dealing with biochemical data, increasing our understanding of the mechanisms underlying diseases. Our findings should be extended and complemented with other omics data such as proteomics and genomics, which could provide a much greater understanding of thyroid dysfunction and associated lipid imbalances.
Full paper open access here:
