The macronutrient composition (MNC) of the habitual diet may affect cardiometabolic disease (CMD) risk. Historically, high fat content has been considered a main dietary risk factor for CMD disease incidence. This hypothesis has been rebutted by trials detecting no significant health benefits of long-term low-fat diet interventions. Conversely, Mediterranean diet (MedD) intervention trials with high unsaturated plant fat intake (especially, extra virgin olive oil) have demonstrated substantial prevention of diabetes and cardiovascular events. In addition, some studies show that low-carbohydrate diet (LCD) may support body weight reduction and type 2 diabetes management. These results suggest that the high carbohydrate (CHO) content of modern diets may contribute to the obesity epidemic and associated CMD diseases. However, the long-term effects of LCD on CMD risk remain elusive. In addition, macronutrient quality (MNQ) is a critical CMD risk determinant. Substitution of saturated animal fat with mono- and polyunsaturated fatty acids from unrefined plant oils is related to low CMD risk.6 Observational studies defined a healthy (i.e., dietary guideline concordant) LCD index (hLCD, high unsaturated fat, plant protein, and low sugar and refined grain intake) and a unhealthy LCD index (uLCD, higher saturated fat, animal protein, and low wholegrain intake). A high hLCD index was associated with low CMD risk and mortality, but high uLCD index with high CMD risk. Metabolic profiling studies in prospective cohorts may elucidate the metabolic pathways that link dietary MNC and MNQ to CMD risk. Furthermore, the optimal MNC and MNQ may differ between individuals depending on the gut microbiome composition. Multi-omics profiling in prospective cohorts may generate objective multi-metabolite biomarkers to assess the metabolic response to dietary MNC and MNQ and predict the subgroup-specific long-term health impact. Aim 1: Derive MMS of dietary MNC and MNQ and examine their association with the risk of incident type 2 diabetes, cardiovascular diseases (myocardial infarction and stroke), and cause-specific mortality. a. Derive dietary indices that reflect the macronutrient composition (e.g., LCD) and both quality and composition (hLCD, uLCD) of the self-reported habitual diet and use machine learning from untargeted metabolomics data to build MMS that predict dietary index adherence. Hypothesis: MMS of beneficial dietary indices are enriched with UFA-containing lipids and secondary plant metabolites. b. Associate dietary indices and MMSs of dietary MNC and MNQ with CMD risk (diabetes, coronary heart disease, stroke, and cause-specific mortality) and asses to what extent MMSs mediate potential associations of the dietary indices with disease incidence. Hypothesis: MMS of beneficial dietary indices (e.g., hLCD, CQI) are related to low CMD risk, whereas MMS of unfavorable dietary indeces (e.g., uLCD, GL) are related to higher risk. Aim 2: Examine if the composition and functional capacity of the gut microbiome mediate or modify the potential effect of dietary MNC and MNQ with prospective CMD risk. We hypothesize that the relationship between dietary MNC and MNQ with cardiometabolic health depend on the gut microbiome’s functional capacity.