Advances in grain research illuminate potential for precision nutrition in clinical settings

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Grains are a primary source of energy (calories) in food. In addition, they provide a large amount of macronutrients, micronutrients, minerals, fiber and phytochemicals.

These nutrients are essential for maintaining the balance of various essential human organs and metabolic processes.

A recent editorial from nutrients The journal emphasized the importance of detailed research on the health benefits of eating different grains.

It is worth noting that worldwide dietary patterns are diverse, reflecting regional food traditions.

Study: Grain Intake and Cardiometabolic Health - Towards Precision Nutrition.  Image credit: pbd Studio/Shutterstock.comStudy: Grain intake and cardiometabolic health—towards precision nutrition. Image credit: pbd Studio/

Crop health benefits

Meta-analyses on the health benefits of whole grains consistently suggest that their consumption is associated with a reduced risk of cardiovascular disease (CVD), type 2 diabetes (T2D), and overall mortality.

However, the health effects of different types of grains, such as refined grains such as white rice, remain underexplored or conflicting data, especially when considering cooking methods.

For example, although popcorn has a high glycemic index and trans fat content, studies in the US have linked its consumption to positive effects on T2D and heart disease.

Similarly, some porridges, even whole grains such as millet, may contain minimal whole grains and have a high glycemic index, reducing potential epidemiological consequences.

Because of dietary habits, gut microbiota profiles, and the relationship between diet and cardiometabolic health, the effects of grain consumption may also differ among individuals with unique health conditions, possibly due to dietary variation.

As an example, dried beans have been found to reduce the risk of high blood pressure in constipated patients.

Recent studies using high-throughput omics methods have enriched our understanding of biological disturbances associated with various dietary patterns and environmental exposures.

These studies document changes in metabolic levels and gut microbial species following different grain consumption patterns, highlighting the health benefits of grains.

In a Danish study, participants consuming 179 g/day of whole grains for eight weeks experienced significant reductions in body weight, C-reactive protein (CRP), and serum interleukin (IL)-6 levels, although their fecal microbiomes were unaffected.

A separate N-of-1 trial revealed that a brief six-day high- or low-carbohydrate dietary intervention could alter the species of gut-dwelling fungi (mycobiome) linked to glycemic metrics.

Moreover, oat consumption at 80 g/day for 45 days significantly reduced LDL and total cholesterol levels in Chinese participants with mild hypercholesterolemia. These participants also exhibited changes in metabolite levels across several pathways, such as sphingosine and phosphatidylcholine.

An intervention involving the addition of resistant starch wheat to the diet of healthy adults showed that it affected the frequencies of faecal butyrate-producing bacteria and other short-chain fatty acid (SCFA) producers, which play a role in gastrointestinal health.

Furthermore, the Pounds Lost trial indicates that individuals with different genotypes may respond differently to carbohydrate intake in relation to weight loss and cardiovascular characteristics.

This trial also suggested that baseline metabolic profiling could predict changes in body composition in response to linoleic acid supplementation.

Machine learning can provide insights into gut microbiome characteristics and baseline metabolome in response to dietary interventions, including grains.

For example, a six-week whole grain intervention can predict weight loss by monitoring the abundance of the gut microbial species Prevotella.

Advances brought about by multi-omics approaches have improved our understanding of the beneficial effects of dietary changes involving modified grains. This progress points to the potential of integrating multi-omics techniques when predicting response to crop interventions.

However, when recommending the health benefits of grains, recommendations should be specific and consider specific grain types, individual health conditions, cooking methods, and daily intake.

In conclusion, accurately predicting individual responses to grain-based dietary interventions holds promise for advancing precision nutrition in clinical settings.

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