Metabolic phenotypes and risk of colorectal cancer: a systematic review and meta-analysis of cohort studies

Association of metabolic obesity phenotypes with risk of overall and site-specific cancers: a systematic review and meta-analysis of cohort studies

BACKGROUND

Adiposity is a known risk factor for certain cancers; however, it is not clear whether the risk of cancer differs between individuals with high adiposity but different metabolic health status. The aim of this systematic literature review and meta-analysis of cohort studies was to evaluate associations between metabolic obesity phenotypes and overall and site-specific cancer risk.

METHODS

PubMed and Embase databases were used to identify relevant cohort studies up to the 6th of June 2023. Random-effects models were used to estimate summary relative risks (SRRs) and 95% confidence intervals (CIs) for the association between metabolic obesity phenotypes and cancer risk. Certainty of evidence was assessed using the Cochrane methods and the GRADE tool. This study is registered with PROSPERO, number CRD42024549511.

RESULTS

A total of 15,556 records were screened, and 31 publications covering 15 unique cohort studies were included in this analysis. Of these studies, 22 were evaluated as being at low risk of bias and 9 at moderate risk of bias. Compared to metabolically healthy normal-weight individuals (MHNW), metabolically unhealthy overweight/obese (MUOW/OB) individuals had a higher risk of overall (SRR = 1.21, 95% CI = 1.02-1.44, n = 3 studies, high certainty) and obesity-related cancers (SRR = 1.42, 95% CI = 1.15-1.74, n = 3, very low certainty). Specifically, MUOW/OB individuals were at higher risk of cancers of the postmenopausal breast (SRR = 1.32, 95% CI = 1.17-1.48, n = 7, low certainty), colorectum (SRR = 1.24, 95% CI = 1.16-1.31, n = 6, moderate certainty), endometrium (SRR = 2.31, 95% CI = 2.08-2.57, n = 4, high certainty), thyroid (SRR = 1.42, 95% CI = 1.29-1.57, n = 4, moderate certainty), kidney (SRR = 1.71, 95% CI = 1.40-2.10, n = 3, low certainty), pancreas (SRR = 1.35, 95% CI = 1.24-1.47, n = 3, high certainty), liver (SRR = 1.81, 95% CI = 1.36-2.42, n = 2, moderate certainty), gallbladder (SRR = 1.42, 95% CI = 1.17-1.73, n = 2, high certainty), bladder (SRR = 1.36, 95% CI = 1.19-1.56, n = 2, moderate certainty), and stomach (SRR = 1.50, 95% CI = 1.12-2.01, n = 2, high certainty). In addition, we found elevated risks of most of these cancers among individuals classified as MUNW and MHOW/OB phenotypes compared to those with MHNW phenotype. Our stratified analyses according to metabolic obesity phenotypes suggested that the elevated risks of some cancers were stronger in individuals with MUOW/OB versus those with MHOW/OB or MUNW phenotypes.

CONCLUSION

These findings suggest that both higher adiposity and metabolic dysfunction were independently associated with increased risk of several cancers, with the strongest associations generally observed among those with both metabolic dysfunction and obesity.

Metabolic risk factors of colorectal cancer: Umbrella review

BACKGROUND AND AIM

The association between metabolic factors and colorectal cancer (CRC) risk is inconclusive. This umbrella review aimed to summarise and describe the association using existing systematic reviews and/or meta-analyses.

METHOD

Four databases (Medline, Scopus, Web of Science, and Cochrane Library) were searched for systematic reviews and/or meta-analyses of observational studies. Two independent authors extracted data on the summary estimated effect and heterogeneity of studies using I2 from the individual reviews. The Assessing the Methodological Quality of Systematic Reviews (AMSTAR 2) tool was used to evaluate the methodological quality.

RESULTS

49 articles were included in this review. Although most included studies were graded with critically low methodological quality (81.6 %), we found a significant positive association between obesity (summary relative risk (SRR) range 1.19-1.49), diabetes mellitus (SRR range 1.20-1.37), hypertension (SRR range 1.07-1.62), metabolic syndrome (SRR range 1.25-1.36), non-alcoholic fatty liver disease (pooled odds ratio (POR) range 1.13-1.56), and risk of CRC. Higher serum high-density lipoprotein cholesterol levels were associated with a lower risk of CRC in 3/6 reviews, while others did not find any association. There was no clear association between high triglyceride levels, total cholesterol levels, low-density lipoprotein cholesterol levels, and risk of CRC.

CONCLUSION

This umbrella review identified that most metabolic factors are significantly associated with increased risk of CRC. Thus, people affected by metabolic factors may be benefited from CRC screening and surveillance.

Metabolically healthy obesity and health risks - a review of meta-analyses

OBJECTIVE

This article briefly summarizes the results of existing research on metabolically healthy obesity in the context of health risks.

METHODS

The PubMed database was searched for relevant meta-analyses addressing metabolically healthy obesity in the context of health risks.

RESULTS

We included a total of 17 relevant meta-analyses in this review. The results of the studied meta-analyses showed that metabolically healthy obesity may be only a transient condition associated with an increased risk of developing metabolic abnormalities in the future. People with obesity without metabolic abnormalities have an increased risk of type 2 diabetes, cardiovascular disease, cancer, chronic kidney disease, and depressive syndrome. In addition, all people with obesity are at risk of pathogenesis resulting from the mechanical stress caused by presence of abnormal adipose tissue, such as sleep apnoea syndrome or skin problems.

CONCLUSION

Based on the results of meta-analyses, we recommend motivating all obese patients to change their lifestyle regardless of the presence of metabolic defects.

Macronutrient quality and the incidence of metabolically unhealthy phenotypes in adults with normal weight and overweight/obesity

OBJECTIVE

We aimed to investigate the associations of macronutrient quality indices with the incident metabolically unhealthy normal weight (MUNW) and metabolically unhealthy overweight/obesity (MUO) phenotypes.

METHODS

This prospective study included 512 metabolically healthy normal weight and 787 metabolically healthy overweight/obese adults from the third study examination of the Tehran Lipid and Glucose Study. The participants were followed through the sixth study examination. Diet was measured with a food frequency questionnaire. The macronutrient quality index (MQI), carbohydrate quality index (CQI), fat quality index (FQI), and healthy plate quality index (HPPQI) were calculated. Hazard ratio (HR) and 95 % confidence interval (95 % CI) were estimated for incident unhealthy phenotypes using Cox regression.

RESULTS

After controlling all possible confounding factors, a one-point higher HPPQI was linked to a 28 % lower risk of MUNW (HR = 0.72; 95 % CI = 0.59, 0.87). Compared to the lowest quartile, the incident MUNW was also lower in the two last quartiles of the HPPQI. A one-unit increase in MQI was associated with a 5 % lower incident MUO (HR = 0.95; 95 % CI = 0.92, 0.99). The incident MUO was also higher for the highest compared to the lowest MQI quartile. In quartiles 2-4 of the HPPQI, incident MUO was lower with respective HRs (95 % CI) of 0.71 (0.54, 0.93), 0.60 (0.45, 0.80), and 0.66 (0.50, 0.86) in the fully-adjusted model.

CONCLUSIONS

A higher overall macronutrient quality was independently associated with a lower incident MUO. A higher dietary protein quality was related to a lower risk for MUNW and MUO.

Why Does Obesity as an Inflammatory Condition Predispose to Colorectal Cancer?

Obesity is a complex and multifactorial problem of global importance. Additionally, obesity causes chronic inflammation, upregulates cell growth, disturbs the immune system, and causes genomic instability, increasing the risk of carcinogenesis. Colorectal cancer is one of the most common cancers, and it has become a global problem. In 2018, there were around 1.8 million new cases and around 881,000 deaths worldwide. Another risk factor of colorectal cancer associated with obesity is poor diet. A Western diet, including a high intake of red and processed meat and a low consumption of whole grains, fruits, vegetables, and fiber, may increase the risk of both colorectal cancer and obesity. Moreover, the Western diet is associated with a proinflammatory profile diet, which may also affect chronic low-grade inflammation. In fact, people with obesity often present gut dysbiosis, increased inflammation, and risk of colorectal cancer. In this article, the association between obesity and colorectal cancer is discussed, including the most important mechanisms, such as low-grade chronic inflammation, gut dysbiosis, and poor diet.

Metabolic syndrome, obesity and cancer risk

PURPOSE OF REVIEW

This review aims to report the latest discoveries regarding the relationship between BMI, obesity, and cancer development and treatment.

RECENT FINDINGS

Obesity and metabolic syndrome relationships with cancer have been deeply investigated in the literature but their association is still debated. Currently, it has been recorded an association between BMI and endometrial, colorectal, gastric, liver, bladder, and prostate cancer. The mechanisms behind this association have also been investigated. It has been hypothesized that chronic inflammation determined by obesity may concur to the development of tumors and that Insulin Resistance may enhance cell proliferation directly or indirectly. Moreover, different studies suggest that the relationship between higher BMI and cancer may include metabolic disturbances comparable to those linked to metabolic syndrome. However, greater weight has been linked to a better overall prognosis in patients with advanced disease, a concept called the obesity paradox. This paradox has been recently investigated in the context of urological malignancies, such as bladder, prostate, and kidney cancer.

SUMMARY

Patients' metabolic and morphological status may impact their risk of developing different types of tumors and the response to systemic therapy. However, further research is necessary to better delineate the mechanisms behind these associations and how they could or should affect medical decision.