Table 2.

Main findings of the omics studies in adults

Ref.	Study design	Population (n)	Main findings
Ge et al[34]	Community-based case-control study	511 healthy adults, mean age 47.9 yr	76 patients had increased FPG and 435 had decreased or fluctuant FPG. Nine SNPs in five genes were significantly associated with increased FPG. Among the 24 glycan peaks identified, GPs 3, 8 and 11 had a positive trend with increased FPG levels, while opposite findings were found for GPs 4 and 14
Peterson et al[36]	Double-blind, randomized, placebo-controlled, parallel design study	65 adults aged 30-65 yr	Fenofibrate treatment lowered C24:0/C16:0 plasma ratio and minimally altered oxidative stress markers and correlated with worse diastolic function. Plasma TG lowering correlated with improvement in diastolic function
Yun et al[35]	Prospective study	1974 adults, aged 50-70 yr	During the 6 yr follow-up, 529 participants developed T2D. 14 sphingolipids (3 reported and 11 novel) were positively associated with incident T2D. WGCNA analysis generated 5 modules, containing different species of sphingolipids; of these, 2 modules containing saturated sphingomyelins showed the strongest association with increased T2D risk
Sun et al[38]	Systematic review	33 studies on the application of metabolomics to disease related-risk. 5 studies on the applications of metabolomics for disease prediction. 5 studies on the applications of metabolomics biomarkers for disease intervention. 8 studies about the integration of genomic and metabolomics data	The first 33 studies find out different metabolites associated with T2D, heart failure, IR and MetS. Studies about the disease prediction demonstrated that some metabolites (amino acids and lipids) were predictive for T2D. Studies about the applications of biomarkers investigated the effect of diet in reducing some risk factors. Studies on the integration of genomic and metabolomics data reported some allele positively associated with high levels of risk metabolites
Misra and Misra[2]	Systematic review	18 studies about heavy metals. 14 studies about persistent organic pollutants and pesticides. 7 studies about drugs and pharmaceuticals. 11 studies about atmospheric pollution	Heavy metals (e.g., arsenic, lead, selenium and mercury) were positively associated with increased T2D risk. Some pollutants of the POPs and pesticides’ family were directly associated with increased risk of developing T2D. Drugs such as antibiotics, antidepressant or antipsychotics were positively associated with increased T2D risk. Long exposure to atmospheric pollutants such as NO2 and PM2.5 were directly associated with T2D
Zhang et al[39]	Cohort study	694 patients (491 HIV-infected and 203 HIV-uninfected) aged 35-55 yr	11 lipids species were identified and associated with T2D risk. No association of HIV status with higher T2D risk was found, while ART use was associated with 8 risk lipids (3 decreased-risk lipids and 5 higher-risk lipids)
Wang et al[40]	Systematic review complication	1 study about application of proteomics in T2D. 1 study about the application of metabolomics in T2D. 1 study about the application of metagenomics in T2D	Proteomics analyses on 62 Mexican T2D patients showed 113 proteins related to T2D risk; in particular, 3 of these have been associated with obesity and T2D while 1 was associated with anti-inflammatory pathways. Metabolomics analyses found 33 metabolites strongly related to T2D. Metagenomics analyses reported different gut microbiota profiles between fecal sample of T2D patients and control subjects
Gudmundsdottir et al[41]	Prospective cohort study	2916 European patients (789 diabetic patients and 2127 non diabetic patients at high T2D risk development)	55 modules of coexpressed genes in the whole blood of the nondiabetic cohort were found. These modules were associated with inflammation, fat tissues, glucose tolerance, insulin sensitivity, and C-reactive protein levels, and were also preserved between non-diabetic and newly diagnosed T2D cohort
Gu et al[42]	Observational study	72 patients (30 normal weight, 26 obese and 16 newly T2D diagnosed)	Obese patients showed upregulation of 78 metabolites and downregulation of 111 metabolites than lean subjects. T2D patients showed upregulation of 459 metabolites and downregulation of 166 metabolites compared to obese subjects. Several metabolites, including amino acids and amino acids metabolites, were identified as IR potential biomarkers
Diamanti et al[43]	Cohort study	42 subjects (12 healthy controls, 16 with prediabetes and 14 T2D subjects)	Plasma metabolomics profiling revealed a positive association of hepatic fat content with tyrosine and a negative relationship with lysophosphatidylcholine. Visceral and subcutaneous adipose tissue insulin sensitivity was positively associated with several lysophospholipids, while the opposite was found for branched-chain amino acids. Several metabolites were significantly higher in T2D subjects than normal/prediabetes subjects
Salihovic et al[44]		1424 adult subjects	Three out of 62 identified metabolites were associated with prevalent T2D (mainly lower urine levels of 3-hydroxyundecanoyl-carnitine). In participants without T2D at baseline, 6 metabolites improving T2D prediction were identified

T2D: Type 2 diabetes; FPG: Fasting plasma glucose; SNP: Single nucleotide polymorphism; TG: Triglycerides; IR: Insulin resistance; WGCNA: Weighted gene coexpression network analysis.