HDL cholesterol and cancer risk among patients with type 2 diabetes

Causal association of smoking, blood lipids, and bladder cancer: Insights from a multivariable and mediation mendelian randomization investigation

We used Mendelian randomization (MR) to examine the relationship between smoking, various categories of blood lipids, and bladder cancer (BLCA). Data for this study were drawn from the genome-wide association studies of the GSCAN consortium (~1.2 million participants), a subset of the UK Biobank (~120,000 participants), and the FinnGen consortium (2,072 cases and 307,082 controls). Initially, we utilized inverse variance weighted (IVW), complementary and sensitivity analyses, multivariable MR, and meta-analysis to confirm the association between blood lipids and BLCA. We then performed mediation MR to elucidate the relationship between smoking, blood lipids, and BLCA. Our analysis identified five lipids, including triglycerides in very large HDL, cholesterol in small VLDL, free cholesterol in very large HDL, total free cholesterol, and apolipoprotein B, as having strong and inverse associations with BLCA. These lipids demonstrated no heterogeneity or pleiotropy and exhibited consistent direction and magnitude across IVW, weighted median, and MR-Egger analyses. Our mediation MR further revealed that triglycerides in very large HDL and cholesterol in small VLDL could reduce the impact of smoking on BLCA, mediating -4.3% and -4.5% of the effect, respectively. In conclusion, our study identified five lipids exhibiting a robust inverse relationship with BLCA, two of which can buffer the impact of smoking on BLCA.

Prognostic and therapeutic value of serum lipids and a new IPI score system based on apolipoprotein A-I in diffuse large B-cell lymphoma

Lipid metabolism is associated with lymphomagenesis and functions as a new therapeutic target in patients with lymphoma. Several serum lipids and lipoproteins have prognostic value in solid tumors; however, their value in diffuse large B-cell lymphoma (DLBCL) has been poorly described. We retrospectively analyzed and compared pre-treatment serum lipid and lipoprotein levels, including triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-I (ApoA-I), and apolipoprotein B (ApoB) between 105 DLBCL and 105 controls (no DLBCL). The prognostic significance of serum lipid and lipoprotein levels was determined using univariate and multivariate Cox proportional hazards models. The primary outcomes, overall survival (OS) and progression-free survival (PFS), were assessed by the Kaplan-Meier method. We combined the International Prognostic Index (IPI) with ApoA-I to build a nomogram model (IPI-A) to predict the OS and PFS of DLBCL. Serum TG, LDL-C, HDL-C, ApoA-I, and ApoB levels were significantly lower in the DLBCL patients than in controls and significantly increased after chemotherapy. Multivariate analyses showed that the ApoA-I level was an independent predictor of OS and PFS. In addition, our findings indicated that the prognostic index IPI-A significantly improves risk prediction over the traditional IPI score system. ApoA-I is an independent prognostic factor associated with poor OS and PFS in DLBCL patients. Our findings suggested that IPI-A is a prognostic index accurately used for risk assessment in patients with DLBCL.

Role of Serum Lipids, Blood Glucose and Blood Pressure in Breast Cancer Risk for Women with Type 2 Diabetes Mellitus

PURPOSE

Women with type 2 diabetes mellitus (T2DM) have an increased risk of breast cancer. We aimed to determine the contribution of lipids, glucose and blood pressure to this risk based on the multifactorial nature of T2DM.

PATIENTS AND METHODS

This population-based cohort study used data from a Dutch database (the Groningen Initiative to Analyse Type 2 Diabetes Treatment) for the period 2004-2013. The cohort included women diagnosed with T2DM, aged 30-80 years, with no history of breast cancer and with follow-up data for at least 1 year. We used Cox proportional hazards models to estimate the associations of exposures with breast cancer occurrence, reporting adjusted hazard ratios (aHR) with 95% confidence intervals (CI). Exposures of interest included total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides, glycated hemoglobin A (HbA1c) and systolic blood pressure (SBP).

RESULTS

During a median of 4.45 years' follow-up, 183 of 10,183 included women received a breast cancer diagnosis. We observed U-shaped associations with breast cancer incidence for total cholesterol and HDL-C at baseline. Compared with moderate elevations, women had significantly higher breast cancer risks associated with high total cholesterol (aHR, 95% CI: 1.72, 1.15-2.55) and HDL-C (aHR, 95% CI: 1.74, 1.18-2.58) levels, while low total cholesterol (aHR, 95% CI: 1.43, 0.94-2.19) and HDL-C (aHR, 95% CI: 1.44, 0.95-2.17) levels produced marginal effects without significance. Women with high LDL-C levels more often received a breast cancer diagnosis than those with medium levels (aHR, 95% CI: 1.56, 1.03-2.35).

CONCLUSION

This real-world dataset highlights the importance of balancing lipid profiles, particularly total cholesterol and HDL-C. Dysregulation of the lipid profile, not the glucose or blood pressure profiles, may increase the risk of breast cancer in women with T2DM.

Low HDL-cholesterol levels predict hepatocellular carcinoma development in individuals with liver fibrosis

Background & Aims

Dysmetabolic conditions could drive liver fibrosis in patients with non-alcoholic fatty liver disease (NAFLD), increasing susceptibility to hepatocellular carcinoma (HCC). We therefore aimed to identify novel predictive biomarkers of HCC in patients with and without liver fibrosis.

Methods

A total of 1,234 patients with putative metabolic conditions and NAFLD were consecutively assessed in our outpatient clinic. Clinical and biochemical data were recorded, and then liver ultrasonography was performed annually for 5 years to detect HCC onset. For the analysis, the population was first divided according to HCC diagnosis; then a further subdivision of those who did not develop HCC was performed based on the presence or absence of liver fibrosis at time 0.

Results

Sixteen HCC cases were recorded in 5 years. None of our patients had been diagnosed with cirrhosis before HCC was detected. Compared to patients who did not develop HCC, those who did had higher liver transaminases and fibrosis scores at time 0 (p <0.001). In addition, they presented with increased glycated haemoglobin levels and lower 25-OH vitamin D levels (p <0.05). Intriguingly, patients with higher liver fibrosis scores who subsequently developed HCC had lower HDL-cholesterol (HDL-c) levels at time 0 (p <0.001). Furthermore, in the 484 patients presenting with lower HDL-c at baseline, we found that waist circumference, and then vitamin D and glycated haemoglobin levels, were significantly different in those who developed HCC, regardless of liver fibrosis (p <0.05).

Conclusions

This study identifies HDL-c as a bona fide novel marker to predict HCC in patients with NAFLD. Increased waist circumference and deranged metabolic pathways represent additional predisposing factors among patients with low HDL-c, highlighting the importance of studying cholesterol metabolism and integrating clinical approaches with dietary regimens and a healthy lifestyle to prevent HCC.

Impact and implications

Visceral adiposity and its associated conditions, such as chronic inflammation and insulin resistance, may play a pivotal role in hepatocellular carcinoma development in patients with non-alcoholic fatty liver disease. We provide new insights on the underlying mechanisms of its pathogenesis, shedding light on the involvement of low levels of "good" HDL-cholesterol. We recommend integrating dietary regimens and advice on healthy lifestyles into the clinical management of non-alcoholic fatty liver disease, with the goal of reducing the incidence of hepatocellular carcinoma.

Repeated Low High-Density Lipoprotein Cholesterol and the Risk of Thyroid Cancer: A Nationwide Population- Based Study in Korea

BACKGROUND

High-density lipoprotein cholesterol (HDL-C) plays an important role in the reverse cholesterol transport pathway and prevents atherosclerosis-mediated disease. It has also been suggested that HDL-C may be a protective factor against cancer. However, an inverse correlation between HDL-C and cancer has not been established, and few studies have explored thyroid cancer.

METHODS

The study participants received health checkups provided by the Korean National Health Insurance Service from 2009 to 2013 and were followed until 2019. Considering the variability of serum HDL-C level, low HDL-C level was analyzed by grouping based on four consecutive health checkups. The data analysis was performed using univariate and multivariate Cox proportional hazard regression models.

RESULTS

A total of 3,134,278 total study participants, thyroid cancer occurred in 16,129. In the crude model, the hazard ratios for the association between repeatedly measured low HDL-C levels and thyroid cancer were 1.243, 1.404, 1.486, and 1.680 (P for trend <0.01), respectively, which were significant even after adjusting for age, sex, lifestyle factors, and metabolic diseases. The subgroup analysis revealed that low HDL-C levels likely had a greater impact on the group of patients with central obesity (P for interaction= 0.062), high blood pressure (P for interaction=0.057), impaired fasting glucose (P for interaction=0.051), and hyperlipidemia (P for interaction=0.126).

CONCLUSION

Repeatedly measured low HDL-C levels can be considered a risk factor for cancer as well as vascular disease. Low HDL-C levels were associated with the risk of thyroid cancer, and this correlation was stronger in a metabolically unhealthy population.

A global assessment of recent trends in gastrointestinal cancer and lifestyle-associated risk factors

Background

Gastrointestinal (GI) cancers were responsible for 26.3% of cancer cases and 35.4% of deaths worldwide in 2018. This study aimed to analyze the global incidence, mortality, prevalence, and contributing risk factors of the 6 major GI cancer entities [esophageal cancer (EC), gastric cancer (GC), liver cancer (LC), pancreatic cancer (PC), colon cancer, and rectal cancer].

Methods

Using the Global Cancer Observatory and the Global Health Observatory databases, we reviewed the current GI cancer incidence, prevalence, and mortality, analyzed the association of GI cancer prevalence with national human development indices (HDIs), identified the contributing risk factors, and estimated developing age‐ and sex‐specific trends in incidence and mortality.

Results

In 2020, the trend in age‐standardized rate of incidence of GI cancers closely mirrored that of mortality, with the highest rates of LC, EC, and GC in Asia and of colorectal cancer (CRC) and PC mainly in Europe. Incidence and mortality were positively, but the mortality‐to‐incidence ratio (MIR) was inversely correlated with the national HDI levels. High MIRs in developing countries likely reflected the lack of preventive strategies and effective treatments. GI cancer prevalence was highest in Europe and was also positively correlated with HDIs and lifestyle‐associated risk factors, such as alcohol consumption, smoking, obesity, insufficient physical activity, and high blood cholesterol level, but negatively correlated with hypertension and diabetes. Incidences of EC were consistently and those of GC mostly decreasing, whereas incidences of CRC were increasing in most countries/regions, especially in the younger populations. Incidences of LC and PC were also increasing in all age‐gender populations except for younger males. Mortalities were decreasing for EC, GC, and CRC in most countries/regions, and age‐specific trends were observed in PC and LC with a decrease in the younger but an increase in the older population.

Conclusions

On the global scale, higher GI cancer burden was accompanied, for the most part, by factors associated with the so‐called Western lifestyle reflected by high and very high national HDI levels. In countries/regions with very high HDI levels, patients survived longer, and increasing GI cancer cases were observed with increasing national HDI levels. Optimizing GI cancer prevention and improving therapies, especially for patients with comorbid metabolic diseases, are thus urgently recommended.

Low high-density lipoprotein cholesterol levels are associated with malignant intraductal papillary mucinous neoplasms: A multicenter study

BACKGROUND

Intraductal papillary mucinous neoplasms (IPMNs) can potentially undergo malignant transformation. Studies have shown that high-density lipoprotein cholesterol (HDL-c) was associated with the risk of cancer. In this study, the association between HDL-c and the incidence of malignancy in IPMNs was investigated.

MATERIALS AND METHODS

226 patients with histologically proven IPMNs who underwent surgery were included in the present study. Patients were assigned to a training group (n = 151) and validation group (n = 75). Patients' demographic information, clinical data, and histopathological evaluation findings were obtained from medical records. Malignant IPMNs were defined as lesions that showed high grade dysplasia and invasive carcinoma. Logistic regression analyses were used to show the association between HDL-c and malignant IPMNs. Receiver operating characteristic (ROC) curves were generated to analyze predictive performance.

RESULTS

The prevalence of low HDL-c levels was higher in patients with malignant IPMNs than in those with non-malignant IPMNs (P < 0.01) in both the training group and validation group. The prevalence of malignant IPMNs decreased with an increase in HDL-c levels both in patients with all types of IPMNs, as well as in those with branch-duct IPMNs (BD-IPMNs).Logistic analysis showed that low HDL-c levels were associated with malignant IPMNs (odds ratio (OR) = 20.56, 95 % confidence interval (CI): 2.58-163.64, P < 0.01) in all types of IPMNs and BD-IPMNs (OR = 17.6, 95 %CI: 1.16-268.46, P = 0.02 ).The predictive performance of mural nodules plus low HDL-c levels was higher than that of mural nodules alone or mural nodules plus cyst size for the identification of malignant BD-IPMNs.

CONCLUSIONS

HDL-c levels may serve a potential biomarker for identifying malignant IPMNs and improve the predictive ability of malignancy in BD-IPMNs.

Association Between Statins and Cancer Incidence in Diabetes: a Cohort Study of Japanese Patients with Type 2 Diabetes

BACKGROUND

The antitumor effect of statins has been highlighted, but clinical study results remain inconclusive. While patients with diabetes are at high risk of cancer, it is uncertain whether statins are effective for cancer chemoprevention in this population.

OBJECTIVE

This study evaluated the association between statins and cancer incidence/mortality in patients with type 2 diabetes.

DESIGN

This study was a follow-up observational study of the Japanese Primary Prevention of Atherosclerosis with Aspirin for Diabetes (JPAD) trial, which was a randomized controlled trial of low-dose aspirin in Japanese patients with type 2 diabetes.

PARTICIPANTS

This study enrolled 2536 patients with type 2 diabetes, age 30-85 years, and no history of atherosclerotic cardiovascular disease, from December 2002 until May 2005. All participants recruited in the JPAD trial were followed until the day of any fatal event or July 2015. We defined participants taking any statin at enrollment as the statin group (n = 650) and the remainder as the no-statin group (n = 1886).

MAIN MEASURES

The primary end point was the first occurrence of any cancer (cancer incidence). The secondary end point was death from any cancer (cancer mortality).

KEY RESULTS

During follow-up (median, 10.7 years), 318 participants developed a new cancer and 123 died as a result. Cancer incidence and mortality were 10.5 and 3.7 per 1000 person-years in the statin group, and 16.8 and 6.3 per 1000 person-years in the no-statin group, respectively. Statin use was associated with significantly reduced cancer incidence and mortality after adjustment for confounding factors (cancer incidence: adjusted hazard ratio [HR], 0.67; 95% CI, 0.49-0.90, P = 0.007; cancer mortality: adjusted HR, 0.60; 95% CI, 0.36-0.98, P = 0.04).

CONCLUSIONS

Statin use was associated with a reduced incidence and mortality of cancer in Japanese patients with type 2 diabetes.

Development of a novel lipid metabolism-based risk score model in hepatocellular carcinoma patients

Background

Liver cancer is one of the most common malignancies worldwide. HCC (hepatocellular carcinoma) is the predominant pathological type of liver cancer, accounting for approximately 75–85 % of all liver cancers. Lipid metabolic reprogramming has emerged as an important feature of HCC. However, the influence of lipid metabolism-related gene expression in HCC patient prognosis remains unknown. In this study, we performed a comprehensive analysis of HCC gene expression data from TCGA (The Cancer Genome Atlas) to acquire further insight into the role of lipid metabolism-related genes in HCC patient prognosis.

Methods

We analyzed the mRNA expression profiles of 424 HCC patients from the TCGA database. GSEA(Gene Set Enrichment Analysis) was performed to identify lipid metabolism-related gene sets associated with HCC. We performed univariate Cox regression and LASSO(least absolute shrinkage and selection operator) regression analyses to identify genes with prognostic value and develop a prognostic model, which was tested in a validation cohort. We performed Kaplan-Meier survival and ROC (receiver operating characteristic) analyses to evaluate the performance of the model.

Results

We identified three lipid metabolism-related genes (ME1, MED10, MED22) with prognostic value in HCC and used them to calculate a risk score for each HCC patient. High-risk HCC patients exhibited a significantly lower survival rate than low-risk patients. Multivariate Cox regression analysis revealed that the 3-gene signature was an independent prognostic factor in HCC. Furthermore, the signature provided a highly accurate prediction of HCC patient prognosis.

Conclusions

We identified three lipid-metabolism-related genes that are upregulated in HCC tissues and established a 3-gene signature-based risk model that can accurately predict HCC patient prognosis. Our findings support the strong links between lipid metabolism and HCC and may facilitate the development of new metabolism-targeted treatment approaches for HCC.

[Research Progress on the Relationship between Blood Lipids and Lung Cancer Risk and Prognosis]

近年来，肺癌成为导致癌症相关死亡的主要原因。越来越多证据表明，许多脂类和脂类类似物是肿瘤发生的关键调节因子，吸烟、饮食及肥胖等影响血脂水平的因素可能与癌症的风险相关。目前随着脂质与肿瘤发生过程关系的研究逐渐深入，探索血脂与肺癌风险及预后相关性已成为研究的热点。本文就血脂水平与肺癌发病风险、血脂水平与肺癌患者预后相关性及调整血脂药物与防治肺癌方向的研究进展进行综述。

MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy

The proliferation of genome-wide association studies (GWAS) has prompted the use of two-sample Mendelian randomization (MR) with genetic variants as instrumental variables (IVs) for drawing reliable causal relationships between health risk factors and disease outcomes. However, the unique features of GWAS demand that MR methods account for both linkage disequilibrium (LD) and ubiquitously existing horizontal pleiotropy among complex traits, which is the phenomenon wherein a variant affects the outcome through mechanisms other than exclusively through the exposure. Therefore, statistical methods that fail to consider LD and horizontal pleiotropy can lead to biased estimates and false-positive causal relationships. To overcome these limitations, we proposed a probabilistic model for MR analysis in identifying the causal effects between risk factors and disease outcomes using GWAS summary statistics in the presence of LD and to properly account for horizontal pleiotropy among genetic variants (MR-LDP) and develop a computationally efficient algorithm to make the causal inference. We then conducted comprehensive simulation studies to demonstrate the advantages of MR-LDP over the existing methods. Moreover, we used two real exposure-outcome pairs to validate the results from MR-LDP compared with alternative methods, showing that our method is more efficient in using all-instrumental variants in LD. By further applying MR-LDP to lipid traits and body mass index (BMI) as risk factors for complex diseases, we identified multiple pairs of significant causal relationships, including a protective effect of high-density lipoprotein cholesterol on peripheral vascular disease and a positive causal effect of BMI on hemorrhoids.

HDL in Endocrine Carcinomas: Biomarker, Drug Carrier, and Potential Therapeutic

High-density lipoprotein (HDL) have long been studied for their protective role against cardiovascular diseases, however recently relationship between HDL and cancer came into focus. Several epidemiological studies have shown an inverse correlation between HDL-cholesterol (HDL-C) and cancer risk, and some have even implied that HDL-C can be used as a predictive measure for survival prognosis in for specific sub-population of certain types of cancer. HDL itself is an endogenous nanoparticle capable of removing excess cholesterol from the periphery and returning it to the liver for excretion. One of the main receptors for HDL, scavenger receptor type B-I (SR-BI), is highly upregulated in endocrine cancers, notably due to the high demand for cholesterol by cancer cells. Thus, the potential to exploit administration of cholesterol-free reconstituted or synthetic HDL (sHDL) to deplete cholesterol in endocrine cancer cell and stunt their growth of use chemotherapeutic drug loaded sHDL to target payload delivery to cancer cell has become increasingly attractive. This review focuses on the role of HDL and HDL-C in cancer and application of sHDLs as endocrine cancer therapeutics.

Dose-response relation between serum total cholesterol levels and overall cancer risk: evidence from 12 prospective studies involving 1,926,275 participants

This study aimed to clarify the association between serum total cholesterol (TC) levels and overall cancer risk. Study-specific relative risks (RR) and 95% confidence intervals (CI) were pooled using a random-effects model, and dose-response relation was also evaluated. Twelve prospective studies were identified with a total of 1,926,275 participants and 13,1676 cases. High levels of serum TC showed an inverse association with overall cancer risk (RR for the highest versus the lowest category: 0.87, 95% CI: 0.83 ∼ 0.90; I² = 52.5%). A linear dose-response relation between serum TC levels and overall cancer risk was found (p = .004 for Wald test; I² = 49.6%), and the pooled RR was 0.92 (95% CI: 0.89 ∼ 0.94) for 3 mmol/L, 0.86 (95% CI: 0.81 ∼ 0.90) for 5 mmol/L, 0.80 (95% CI: 0.74 ∼ 0.87) for 7 mmol/L. Our dose-response meta-analysis of 12 prospective studies indicated that higher serum TC levels were significantly associated with reduced cancer risk.

High-density lipoprotein cholesterol and causes of death in chronic kidney disease

BACKGROUND

Recent data suggest a U-shaped association between high-density lipoprotein cholesterol (HDL-c) and death in chronic kidney disease (CKD). However, whether the increased mortality in patients with extreme levels is explained by specific causes of death remains unclear.

OBJECTIVES

We studied the associations between HDL-c and cause-specific deaths in CKD.

METHODS

We included 38,377 patients with estimated glomerular filtration rate 15-59 mL/min/1.73 m². We classified deaths into 3 major categories: (1) cardiovascular; (2) malignant; and (3) noncardiovascular/nonmalignant causes. We fitted Cox regression models for overall mortality and separate competing risk models for each major cause of death category to evaluate their respective associations with categories of HDL-c (≤30, 31-40, 41-50 [referent], 51-60, >60 mg/dL). Separate analyses were conducted for men and women.

RESULTS

During a median follow-up of 4.5 years, 9665 patients died. After adjusting for relevant covariates, in both sexes, HDL-c 31 to 40 mg/dL and ≤30 mg/dL were associated with higher risk of all-cause mortality, cardiovascular mortality, malignancy-related deaths, and noncardiovascular/nonmalignancy-related deaths. HDL-c >60 mg/dL was associated with lower all-cause (hazard ratio: 0.75, 95% confidence interval: 0.69, 0.81), cardiovascular, malignancy-related, and noncardiovascular/nonmalignancy-related deaths among women but not in men. Similar results were noted when HDL-c was examined as a continuous measure.

CONCLUSIONS

In a non-dialysis-dependent CKD population, HDL-c ≤40 mg/dL was associated with risk of higher all-cause, cardiovascular, malignant, and noncardiovascular/nonmalignant mortality in men and women. HDL >60 mg/dL was associated with lower risk of all-cause, cardiovascular, malignant, and noncardiovascular/nonmalignant mortality in women but not in men.

Evolutionarily derived networks to inform disease pathways

Methods to identify genes or pathways associated with complex diseases are often inadequate to elucidate most risk because they make implicit and oversimplified assumptions about underlying models of disease etiology. These can lead to incomplete or inadequate conclusions. To address this, we previously developed human phenotype networks (HPN), linking phenotypes based on shared biology. However, such visualization alone is often uninterpretable, and requires additional filtering. Here, we expand the HPN to include another method, evolutionary triangulation (ET). ET utilizes the hypothesis that alleles affecting disease risk in multiple populations are distributed consistently with differences in disease prevalence and compares allele frequencies among populations and their relationship to phenotype prevalence. We hypothesized that combining these methods will increase our ability to detect genetic patterns of association in complex diseases. We combined HPN and ET to identify network patterns associated with type 2 diabetes mellitus (T2DM), a leading cause of death worldwide. Fasting glucose, a continuous trait, was used as a proxy for T2DM and differs significantly among continental populations. The combined method identified several diabetes-related traits and several phenotypes related to cardiovascular diseases, for which diabetes is a major risk factor. ET-HPN found more phenotypes related to our target and related phenotypes than the application of either method alone. Not only could we detect phenotype connections related to T2DM, but we also identified phenotypes that are distributed in parallel to it, e.g., amyotrophic lateral sclerosis. Our analyses showed that ET-filtered HPN provides information that neither technique can individually.

Blood lipids profile and lung cancer risk in a meta-analysis of prospective cohort studies

BACKGROUND

Emerging evidence has connected lipid metabolism disturbance with lung diseases, but the relationship between blood lipid profile and lung cancer risk is controversial and inconclusive.

OBJECTIVE

We conducted a meta-analysis of prospective cohort studies to evaluate the relationship between blood lipids profile and lung cancer incidence.

METHODS

Relevant studies were identified by searching PubMed, Cochrane Library, Web of Science, EBSCO, Ovid, CNKI, VIP, and WANGFANG MED through August 2016. Nine prospective cohort studies were included in the meta-analysis, and fixed or random effects model was used to calculate pooled relative risk (RRs). The RR was calculated using either highest vs lowest categories, or upper quantile vs lowest quantile. The thresholds were determined by the authors of each original publication, based on either predefined cut-offs or the distributions within their study population.

RESULTS

Analysis of 18,111 lung cancer cases among 1,832,880 participants showed that serum total cholesterol levels were inverse associated with lung cancer risk (RR = 0.93, 95% confidence interval [CI]: 0.85-1.03). Further analysis considered the lag time and excluded the effects of preclinical cancer, with totally 1,239,948 participants and 14,052 lung cancer cases, found a significantly inverse association between total cholesterol and lung cancer risk (RR = 0.89, 95% CI: 0.83-0.94). Analysis of 3067 lung cancer cases among 59,242 participants found that the high-density lipoprotein cholesterol levels (RR = 0.76, 95% CI: 0.59-0.97) was negatively associated with lung cancer risk and 4673 lung cancer cases among 685,852 participants showed that the total triglyceride (RR = 1.68, 95% CI: 1.44-1.96) was positively associated with lung cancer risk.

CONCLUSION

Cholesterol and fatty acid metabolism might present different and specific mechanism on lung cancer etiology and needs further elucidation.

Genetic association analysis of polymorphisms in PSD3 gene with obesity, type 2 diabetes, and HDL cholesterol

BACKGROUND

The pleckstrin and Sec7 domain-containing 3 (PSD3) gene has been linked to immune diseases. We examined whether the genetic variants within the PSD3 gene are associated with obesity, type 2 diabetes (T2D), and high-density lipoprotein (HDL) cholesterol level.

METHODS

Multiple logistic regression model and linear regression model were used to examine the associations of 259 single nucleotide polymorphisms (SNPs) within the PSD3 gene with obesity and T2D as binary traits, and HDL level as a continuous trait using the Marshfield data, respectively. A replication study of obesity was conducted using the Health Aging and Body Composition (Health ABC) sample.

RESULTS

23SNPs were associated with obesity (p<0.05) in the Marshfield sample and rs4921966 revealed the strongest association (p=3.97×10^-6). Of the 23SNPs, 20 were significantly associated with obesity in the meta-analysis of two samples (p<0.05). Furthermore, 6SNPs revealed associations with T2D in the Marshfield data (top SNP rs12156368 with p=3.05×10^-3); while two SNPs (rs6983992 and rs7843239) were associated with both obesity and T2D (p=0.0188 and 0.023 for obesity and p=8.47×10^-3 and 0.0128 for T2D, respectively). Furthermore, 11SNPs revealed associations with HDL level (top SNP rs13254772 with p=2.79×10^-3) in the Marshfield data; meanwhile rs7009615 was associated with both T2D (p=0.038) and HDL level (p=4.44×10^-3). In addition, haplotype analyses further supported the results of single SNP analysis.

CONCLUSIONS

Common variants in PSD3 were associated with obesity, T2D and HDL level. These findings add important new insights into the pathogenesis of obesity, T2D and HDL cholesterol.

Predictive validity of the ACC/AHA pooled cohort equations in predicting cancer-specific mortality in a National Prospective Cohort Study of Adults in the United States

BACKGROUND

The American College of Cardiology/American Heart Association Task Force on Practice Guidelines recently developed the Pooled Cohort Risk (PCR) equations to predict 10-years risk for a first atherosclerotic cardiovascular disease (ASCVD) event. The predictive validity of these PCR equations on cancer-specific mortality among a national sample of US adults has yet to be evaluated, which was this study's purpose.

METHODS

Data from the 1999-2010 National Health and Nutrition Examination Survey were used, with participants followed through December 31, 2011 to ascertain cancer mortality status via the National Death Index probabilistic algorithm. The analysed sample included 11,171 CVD-free adults (40-79 years). Ten-year risk of a first ASCVD was determined from the PCR equations.

RESULTS

For the entire sample, 849,202 person-months occurred with an incidence rate of 0.31 cancer-specific deaths per 1,000 person-months. The unweighted follow-up duration was 72 months (IQR = 39-114). After adjusting for age, gender, race-ethnicity, physical activity and obesity, those with an elevated ASCVD (≥ 7.5%) whom did not have a history of cancer at baseline had a 71% increased risk of cancer-specific mortality. There was less evidence for this relationship among those with a history of cancer. The individual components of the ASCVD that were predictive of cancer-specific mortality included age and smoking status.

CONCLUSION

Ten-year predicted risk of a first ASCVD event via the PCR equations were significantly associated with cancer-specific mortality in a national sample of US adults (40-79 years) whom were free of cancer and CVD at baseline. In this American adult sample, the PCR equations provide evidence of predictive validity for cancer-specific mortality, particularly among those without cancer.

Candidate gene resequencing to identify rare, pedigree-specific variants influencing healthy aging phenotypes in the long life family study

Background

The Long Life Family Study (LLFS) is an international study to identify the genetic components of various healthy aging phenotypes. We hypothesized that pedigree-specific rare variants at longevity-associated genes could have a similar functional impact on healthy phenotypes.

Methods

We performed custom hybridization capture sequencing to identify the functional variants in 464 candidate genes for longevity or the major diseases of aging in 615 pedigrees (4,953 individuals) from the LLFS, using a multiplexed, custom hybridization capture. Variants were analyzed individually or as a group across an entire gene for association to aging phenotypes using family based tests.

Results

We found significant associations to three genes and nine single variants. Most notably, we found a novel variant significantly associated with exceptional survival in the 3’ UTR OBFC1 in 13 individuals from six pedigrees. OBFC1 (chromosome 10) is involved in telomere maintenance, and falls within a linkage peak recently reported from an analysis of telomere length in LLFS families. Two different algorithms for single gene associations identified three genes with an enrichment of variation that was significantly associated with three phenotypes (GSK3B with the Healthy Aging Index, NOTCH1 with diastolic blood pressure and TP53 with serum HDL).

Conclusions

Sequencing analysis of family-based associations for age-related phenotypes can identify rare or novel variants.

Electronic supplementary material

The online version of this article (doi:10.1186/s12877-016-0253-y) contains supplementary material, which is available to authorized users.

Drug-subphenotype interactions for cancer in type 2 diabetes mellitus

On the basis of data obtained from a prospective cohort of Chinese patients with type 2 diabetes mellitus (T2DM), we discuss cancer subphenotypes (risk factors) in patients with T2DM, which can lead to drug-cancer subphenotype interactions. These subphenotypes include HDL cholesterol levels <1.0 mmol/l, co-occurrence of LDL cholesterol levels <2.8 mmol/l and triglyceride levels <1.7 mmol/l, and co-occurrence of LDL cholesterol levels <2.8 mmol/l and albuminuria. The increased risk of cancer associated with low levels of HDL cholesterol, low LDL cholesterol levels plus low triglyceride levels, and low levels of LDL cholesterol plus albuminuria can be reduced by treatment with metformin, renin-angiotensin system (RAS) inhibitors and statins, respectively. Mechanistic studies support the hypothesis that dysregulation of the 5'-AMP-activated protein kinase pathway and crosstalk between the RAS and insulin-like growth factor 1-cholesterol pathways create a cancer-promoting milieu in patients with T2DM. These findings highlight that in Chinese individuals, multiple pathways are implicated in the link between T2DM and cancer, which can generate multiple subphenotypes as well as drug-subphenotype interactions.