Using a polygenic score of DNA sequence polymorphisms, the authors of this study quantified genetic risk and assessed four healthy lifestyle factors. Among participants at high genetic risk, a ...healthy lifestyle was associated with a reduced risk of coronary disease.
Both genetic and lifestyle factors are key drivers of coronary artery disease, a complex disorder that is the leading cause of death worldwide.
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A familial pattern in the risk of coronary artery disease was first described in 1938 and was subsequently confirmed in large studies involving twins and prospective cohorts.
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Since 2007, genomewide association analyses have identified more than 50 independent loci associated with the risk of coronary artery disease.
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These risk alleles, when aggregated into a polygenic risk score, are predictive of incident coronary events and provide a continuous and quantitative measure of genetic susceptibility.
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The totality of microbial genomes in the gut exceeds the size of the human genome, having around 500-fold more genes that importantly complement our coding potential. Microbial genes are essential ...for key metabolic processes, such as the breakdown of indigestible dietary fibres to short-chain fatty acids, biosynthesis of amino acids and vitamins, and production of neurotransmitters and hormones. During the last decade, evidence has accumulated to support a role for gut microbiota (analysed from faecal samples) in glycaemic control and type 2 diabetes. Mechanistic studies in mice support a causal role for gut microbiota in metabolic diseases, although human data favouring causality is insufficient. As it may be challenging to sort the human evidence from the large number of animal studies in the field, there is a need to provide a review of human studies. Thus, the aim of this review is to cover the current and future possibilities and challenges of using the gut microbiota, with its capacity to be modified, in the development of preventive and treatment strategies for hyperglycaemia and type 2 diabetes in humans. We discuss what is known about the composition and functionality of human gut microbiota in type 2 diabetes and summarise recent evidence of current treatment strategies that involve, or are based on, modification of gut microbiota (diet, probiotics, metformin and bariatric surgery). We go on to review some potential future gut-based glucose-lowering approaches involving microbiota, including the development of personalised nutrition and probiotic approaches, identification of therapeutic components of probiotics, targeted delivery of propionate in the proximal colon, targeted delivery of metformin in the lower gut, faecal microbiota transplantation, and the incorporation of genetically modified bacteria that express therapeutic factors into microbiota. Finally, future avenues and challenges for understanding the interplay between human nutrition, genetics and microbial genetics, and the need for integration of human multi-omic data (such as genetics, transcriptomics, epigenetics, proteomics and metabolomics) with microbiome data (such as strain-level variation, transcriptomics, proteomics and metabolomics) to make personalised treatments a successful future reality are discussed.
Apolipoproteins, lipids and risk of cancer Borgquist, Signe; Butt, Talha; Almgren, Peter ...
International journal of cancer,
June 01 2016, Volume:
138, Issue:
11
Journal Article
Peer reviewed
Open access
The epidemiological evidence for an obesity‐cancer association is solid, whereas the association between obesity‐associated lipoprotein levels and cancer is less evident. We investigated circulating ...levels of Apolipoprotein A1 (ApoA1), Apolipoprotein B (ApoB), LDL‐cholesterol (LDL‐C) and HDL‐cholesterol (HDL‐C) and association to risk of overall cancer and common cancer forms. The Malmö Diet and Cancer Study, a population‐based prospective cohort study, enrolled 17,035 women and 11,063 men (1991–1996). Incident cancer cases were ascertained by record linkage with the Swedish Cancer Registry until end of follow‐up, January 1, 2012. Baseline serum levels of ApoA1 and ApoB were analyzed for the entire cohort and HDL‐C and LDL‐C levels in 5,281 participants. Hazard ratios, with 95% confidence interval, were calculated using Cox's proportional hazards analysis. In the entire cohort, none of the exposures were related to overall cancer risk (HRadj ApoA1 = 0.98, 95%CI: 0.95,1.01; HRadj ApoB = 1.01, 95%CI: 0.98–1.04). Among men, ApoB was positively associated with cancer risk (HRadj ApoB = 1.06, 95%CI: 1.01,1.10). Female breast cancer risk was inversely associated with ApoB (HRadj = 0.92, 95%CI: 0.86,0.99). Among both genders, ApoA1 was inversely associated with lung cancer risk (HRadj = 0.88, 95%CI: 0.80,0.97), whereas high ApoB increased lung cancer risk (HRadj = 1.08, 95%CI: 0.99,1.18). Colorectal cancer risk was increased with high ApoB (HRadj = 1.08, 95%CI: 1.01,1.16) among both genders. Apolipoprotein levels were not associated with prostate cancer incidence. Circulating levels of apolipoproteins are associated with overall cancer risk in men and across both genders with breast, lung and colorectal cancer risk. Validation of these findings may facilitate future primary prevention strategies for cancer.
What's new?
Obesity and cancer are associated, although the underlying biological mechanisms are not fully understood. In this population‐based study of 28,098 individuals, incidences of overall cancer and breast, lung and colorectal cancers were found to be associated with circulating levels of apolipoproteins A1 and B (ApoB). The nature of the associations varied. Whereas ApoB was positively linked to cancer risk in men, it was inversely associated with breast cancer risk in women. Meanwhile, no association was found for prostate cancer incidence. The findings may improve the understanding of the obesity‐cancer association and help facilitate primary preventive strategies.
Background Apoptosis is central in both diabetes and atherosclerosis, linked to pancreatic beta cell death and plaque progression. Circulating Caspase‐3 has also been associated with diabetes and ...coronary calcium score. Here, we explored if soluble Caspase‐3 (sCaspase‐3) is associated with cardio‐metabolic risk factors and predicts incidence of diabetes and coronary artery disease (CAD).Methods Clinical data and plasma from 4637 individuals from the Malmö Diet and Cancer cohort were studied. Plasma sCaspase‐3 was measured by a Proximity Extension Assay. National registers were used to identify diabetes and CAD events during follow‐up. Type 2 diabetes risk variants and expression quantitative trait loci (eQTL) for sCaspase‐3 were retrieved from the DIAGRAM consortium and the Genotype‐Tissue Expression project. Results HbA1c was the factor with the strongest association with sCaspase‐3 (r = 0.18, P = 1.3x10−36). During follow‐up 666 individuals developed diabetes and 648 individuals suffered from CAD. Increasing sCaspase‐3 was associated with a higher risk of developing diabetes (hazard ratio (HR) 1.18 per 1unit; P = 7 × 10−5) and CAD (HR 1.2 per 1 unit, P = 1 × 10−4) during follow‐up. A genetic variant rs60780116, located upstream of CASP3, showed strong association with type 2 diabetes (OR 1.06, 95%CI 1.04–1.07, P = 8.4 × 10−11). An eQTL was identified between this variant and gene expression of CASP3, where the allele positively correlated with type 2 diabetes was associated with increased CASP3 expression in blood. Conclusions The present study provides evidence for plasma sCaspase‐3 as a marker of cardio‐metabolic risk factors and as a predictor of future diabetes and CAD in a cohort without cardiovascular disease or diabetes at baseline.
Background & Aims Our aims were to develop a method to accurately predict non-alcoholic fatty liver disease (NAFLD) and liver fat content based on routinely available clinical and laboratory data and ...to test whether knowledge of the recently discovered genetic variant in the PNPLA3 gene (rs738409) increases accuracy of the prediction. Methods Liver fat content was measured using proton magnetic resonance spectroscopy in 470 subjects, who were randomly divided into estimation (two thirds of the subjects, n = 313) and validation (one third of the subjects, n = 157) groups. Multivariate logistic and linear regression analyses were used to create an NAFLD liver fat score to diagnose NAFLD and liver fat equation to estimate liver fat percentage in each individual. Results The presence of the metabolic syndrome and type 2 diabetes, fasting serum (fS) insulin, fS-aspartate aminotransferase (AST), and the AST/alanine aminotransferase ratio were independent predictors of NAFLD. The score had an area under the receiver operating characteristic curve of 0.87 in the estimation and 0.86 in the validation group. The optimal cut-off point of −0.640 predicted increased liver fat content with sensitivity of 86% and specificity of 71%. Addition of the genetic information to the score improved the accuracy of the prediction by only <1%. Using the same variables, we developed a liver fat equation from which liver fat percentage of each individual could be estimated. Conclusions The NAFLD liver fat score and liver fat equation provide simple and noninvasive tools to predict NAFLD and liver fat content.
As cardio metabolic disease manifestations tend to cluster in families there is a need to better understand the underlying mechanisms in order to further develop preventive strategies. In fact, ...genetic markers used in genetic risk scores, important as they are, will not be able alone to explain these family clusters. Therefore, the search goes on for the so called
missing heritability
to better explain these associations. Shared lifestyle and social conditions in families, but also early life influences may be of importance. Gene-environmental interactions should be explored. In recent years interest has grown for the role of diet-microbiota associations, as microbiota patterns may be shared by family members. In the Malmö Offspring Study that started in 2013, we have so far been able to examine about 4700 subjects (18–71 years) representing children and grandchildren of index subjects from the first generation, examined in the Malmö Diet Cancer Study during 1991 to 1996. This will provide rich data and opportunities to analyse family traits of chronic disease across three generations. We will provide extensive genotyping and phenotyping including cardiovascular and respiratory function, as well as markers of glucose metabolism. In addition, also cognitive function will be assessed. A 4-day online dietary recall will be conducted and gut as well as oral microbiota analysed. The ambition is to provide one of the first large-scale European family studies with individual data across three generations, which could deepen our knowledge about the role of family traits for chronic disease and its underlying mechanisms.
Obesity is a risk factor for advanced, but not localised, prostate cancer (PCa), and for poor prognosis. However, the detection of localised PCa through asymptomatic screening might influence these ...associations. We investigated height and body mass index (BMI) among 431 902 men in five Swedish cohorts in relation to PCa risk, according to cancer risk category and detection mode, and PCa‐specific mortality using Cox regression. Statistical tests were two‐sided. Height was positively associated with localised intermediate‐risk PCa (HR per 5 cm, 1.03, 95% CI 1.01‐1.05), while overweight and obesity were negatively associated with localised low‐ and intermediate‐risk PCa (HRs per 5 kg/m2, 0.86, 95% CI 0.81‐0.90, and 0.92, 95% CI 0.88‐0.97). However, these associations were partially driven by PCa's detected by asymptomatic screening and, for height, also by symptoms unrelated to PCa. The HR of localised PCa's, per 5 kg/m2, was 0.88, 95% CI 0.83 to 0.92 for screen‐detected PCa's and 0.96, 95% CI 0.90 to 1.01 for PCa's detected through lower urinary tract symptoms. BMI was positively associated with PCa‐specific mortality in the full population and in case‐only analysis of each PCa risk category (HRs per 5 kg/m2, 1.11‐1.22, P for heterogeneity = .14). More active health‐seeking behaviour among tall and normal‐weight men may partially explain their higher risk of localised PCa. The higher PCa‐specific mortality among obese men across all PCa risk categories in our study suggests obesity as a potential target to improve the prognosis of obese PCa patients.
What's new?
While body mass index and height are linked to prostate cancer risk, how these factors are related to specific risk categories, including localized and advanced disease, remains uncertain. In this investigation of body size and prostate cancer risk, height was positively associated with localised, intermediate‐risk prostate cancer, and overweight and obesity were associated with lower risks of localised low‐ and intermediate‐risk prostate cancers. These associations were partially driven by asymptomatic screening, suggesting that increased screening behavior among tall and normal‐weight men contributes to their elevated risk of localised prostate disease. Relatively high prostate cancer‐specific mortality among obese men flags elevated BMI as a key prognostic factor for prostate malignancy.
The extent to which a favorable lifestyle may lower cancer risk in subjects with a family history of cancer is unknown. We conducted a prospective study in two Swedish cohorts, the Malmö Diet and ...Cancer Study (MDCS; n = 25,604) and the Malmö Preventive Project (MPP; n = 16,216). The association between a favorable lifestyle (based on nonsmoking, normal weight, absence of excessive drinking, regular physical activity and healthy diet) and cancer incidence and mortality risk was assessed using Cox regression stratified by family history of cancer (all types). A favorable lifestyle was associated with a 22% (95% confidence interval CI: 18–26%) and 40% (95% CI: 36–44%) lower risk of cancer incidence and mortality, respectively, compared to an unfavorable lifestyle. No significant effect modification by family history was observed but there was a null association between lifestyle and cancer incidence among subjects with two or more affected first‐degree relatives. The observed relative risk estimates comparing an unfavorable with a favorable lifestyle corresponded to standardized 10‐year cancer incidence rates of 11.2 vs. 9.5% in the MDCS, and 4.4 vs. 3.2% in the MPP, and a reduction in 20‐year cancer mortality rate from 11.7% to 7.4% in the MDCS and 6.7% to 3.9% in the MPP. Improved adherence to cancer prevention recommendations may reduce cancer incidence and mortality risk in the general population, however, further studies are needed to assess the impact of lifestyle on cancer incidence among subjects with strong familial or polygenic risk for specific cancers.
What's new?
While healthy lifestyle is associated with reduced cancer risk in the general population, it remains unknown whether lifestyle factors can overcome the affects of nonmodifiable cancer risk factors, including genetic susceptibility. Here, investigation of lifestyle, family history, and cancer incidence in two separate patient cohorts in Sweden suggests that the benefits of a healthy lifestyle can extend to subjects with family history of cancer. Favorable lifestyle reduced cancer risk by 22% and cancer mortality by 40% in the study cohorts, regardless of family cancer history. The findings warrant further investigation of lifestyle impacts on familial cancer incidence.
Aim
The metabolite 3‐carboxy‐4‐methyl‐5‐propyl‐2‐furanpropionic acid (CMPF) is a fatty fish–intake biomarker. We investigated the association between plasma levels of CMPF in relation to gingival ...inflammation and periodontitis case definition, as well as the extent and severity variables.
Materials and Methods
The Malmö Offspring Study is a population‐based study, and the Malmö Offspring Dental Study (MODS) is its dental arm, including periodontal charting. Plasma CMPF was measured using liquid chromatography–mass spectrometry and studied in relation to periodontal diagnosis and parameters using multivariable linear or logistic regression modelling adjusting for age, sex, education, body mass index, fasting glucose, and smoking.
Results
Metabolite data were available for 922 MODS participants. Higher CMPF levels were associated with less gingival inflammation (β = −2.12, p = .002) and lower odds of severe periodontitis (odds ratio OR = 0.74, 95% confidence interval CI: 0.56 to 0.98). Higher CMPF levels were also associated with more teeth (β = 0.19, p = .001), lower number of periodontal pockets (≥4 mm) (β = −1.07, p = .007), and lower odds of having two or more periodontal pockets of ≥6 mm (OR = 0.80, 95% CI: 0.65 to 0.98) in fully adjusted models.
Conclusions
CMPF, a validated biomarker of fatty fish consumption, is associated with less periodontal inflammation and periodontitis. Residual confounding cannot be ruled out, and future studies are warranted.
Objective
To investigate the causal role of cardiometabolic risk factors in osteoarthritis (OA) using associated genetic variants.
Methods
We studied 27,691 adults from the Malmö Diet and Cancer ...Study (MDCS) and replicated novel findings among 376,435 adults from the UK Biobank. Trait‐specific polygenic risk scores for low‐density lipoprotein (LDL) and high‐density lipoprotein (HDL) cholesterol levels, triglyceride levels, body mass index (BMI), fasting plasma glucose (FPG) levels, and systolic blood pressure (BP) were used to test the associations of genetically predicted elevations in each trait with incident OA diagnosis (n = 3,559), OA joint replacement (n = 2,780), or both (total OA; n = 4,226) in Mendelian randomization (MR) analyses in the MDCS, and with self‐reported and/or hospital‐diagnosed OA (n = 65,213) in the UK Biobank. Multivariable MR, MR‐Egger, and weighted median MR were used to adjust for potential pleiotropic biases.
Results
In the MDCS, genetically predicted elevation in LDL cholesterol level was associated with a lower risk of OA diagnosis (odds ratio OR 0.83 95% confidence interval (95% CI) 0.73–0.95 per 1SD increase) and total OA (OR 0.87 95% CI 0.78–0.98), which was supported by multivariable MR for OA diagnosis (OR 0.84 95% CI 0.75–0.95) and total OA (0.87 95% CI 0.78–0.97), and by conventional 2‐sample MR for OA diagnosis (OR 0.86 95% CI 0.75–0.98). MR‐Egger indicated no pleiotropic bias. Genetically predicted elevation in BMI was associated with an increased risk of OA diagnosis (OR 1.65 95% CI 1.14–2.41), while MR‐Egger indicated pleiotropic bias and a larger association with OA diagnosis (OR 3.25 1.26–8.39), OA joint replacement (OR 3.81 95% CI 1.39–10.4), and total OA (OR 3.41 95% CI 1.43–8.15). No associations were observed between genetically predicted HDL cholesterol level, triglyceride level, FPG level, or systolic BP and OA outcomes. The associations with LDL cholesterol levels were replicated in the UK Biobank (OR 0.95 95% CI 0.93–0.98).
Conclusion
Our MR study provides evidence of a causal role of lower LDL cholesterol level and higher BMI in OA.
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