Apolipoprotein A-II: beyond genetic associations with lipid disorders and insulin resistance

2003 ◽  
Vol 14 (2) ◽  
pp. 165-172 ◽  
Author(s):  
Athina-Despina Kalopissis ◽  
Danièle Pastier ◽  
Jean Chambaz
Keyword(s):  
Insulin Resistance ◽  
Genetic Associations ◽  
Lipid Disorders ◽  
Apolipoprotein A

scholarly journals The Role of Metabolic Factors in Renal Cancers

2020 ◽  
Vol 21 (19) ◽  
pp. 7246
Author(s):  
Jacek Rysz ◽  
Beata Franczyk ◽  
Janusz Ławiński ◽  
Robert Olszewski ◽  
Anna Gluba-Brzózka
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Malignant Tumours ◽  
Metabolic Factors ◽  
Lipid Disorders ◽  
Igf System ◽  
Low Body Mass Index ◽  
The Impact

An increasing number of evidence indicates that metabolic factors may play an important role in the development and progression of certain types of cancers, including renal cell carcinoma (RCC). This tumour is the most common kidney cancer which accounts for approximately 3–5% of malignant tumours in adults. Numerous studies indicated that concomitant diseases, including diabetes mellitus (DM) and hypertension, as well as obesity, insulin resistance, and lipid disorders, may also influence the prognosis and cancer-specific overall survival. However, the results of studies concerning the impact of metabolic factors on RCC are controversial. It appears that obesity increases the risk of RCC development; however, it may be a favourable factor in terms of prognosis. Obesity is closely related to insulin resistance and the development of diabetes mellitus type 2 (DM2T) since the adipocytes in visceral tissue secrete substances responsible for insulin resistance, e.g., free fatty acids. Interactions between insulin and insulin-like growth factor (IGF) system appear to be of key importance in the development and progression of RCC; however, the exact role of insulin and IGFs in RCC pathophysiology remains elusive. Studies indicated that diabetes increased the risk of RCC, but it might not alter cancer-related survival. The risk associated with a lipid profile is most mysterious, as numerous studies provided conflicting results. Even though large studies unravelling pathomechanisms involved in cancer growth are required to finally establish the impact of metabolic factors on the development, progression, and prognosis of renal cancers, it seems that the monitoring of health conditions, such as diabetes, low body mass index (BMI), and lipid disorders is of high importance in clear-cell RCC.

BMI, apolipoprotein B/apolipoprotein A-I ratio, and insulin resistance in patients with prolactinomas: a pilot study in a Chinese cohort

Tumor Biology ◽  
2013 ◽  
Vol 34 (2) ◽  
pp. 1171-1176 ◽  
Author(s):  
Xiao-Bing Jiang ◽  
Dong-Sheng He ◽  
Zhi-Gang Mao ◽  
Xiang Fan ◽  
Ni Lei ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Pilot Study ◽  
Apolipoprotein B ◽  
Apolipoprotein A ◽  
Chinese Cohort

Insulin resistance and lipid disorders

2008 ◽  
Vol 3 (6) ◽  
pp. 651-664 ◽  
Author(s):  
Roberto Miccoli ◽  
Cristina Bianchi ◽  
Giuseppe Penno ◽  
Stefano Del Prato
Keyword(s):  
Insulin Resistance ◽  
Lipid Disorders

scholarly journals Influence of multiple apolipoprotein A-I and B genetic variations on insulin resistance and metabolic syndrome in obstructive sleep apnea

2020 ◽  
Author(s):  
Li Xinyi ◽  
Fu Zhihui ◽  
Xu Huajun ◽  
Zou Jianyin ◽  
Zhu Huaming ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Genetic Risk Score ◽  
Cumulative Effect ◽  
Genetic Variations ◽  
Score Distribution ◽  
Genetic Score ◽  
Single Nucleotide ◽  
Apolipoprotein A ◽  
Obstructive Sleep

Abstract Background The relationships between apolipoprotein A-I (APOA-I), apolipoprotein B (APOB) with insulin resistance, metabolic syndrome (MetS) are unclear in OSA. We aimed to evaluate whether the multiple single nucleotide polymorphism (SNP) variants of APOA-I and APOB exert a collaborative effect on insulin resistance and MetS in OSA. Methods Initially, 12 APOA-I SNPs and 30 APOB SNPs in 5,259 subjects were examined. After strict screening, four APOA-I SNPs and five APOB SNPs in 4,007 participants were included. For each participant, the genetic risk score (GRS) was calculated based on the cumulative effect of multiple genetic variants of APOA-I and APOB. Logistic regression analyses were used to evaluate the relationships between APOA-I/APOB genetic polymorphisms, insulin resistance, and MetS in OSA. Results Patients with insulin resistance had a lower APOA-I GRS and higher APOB levels after adjustments [odds ratio (OR) = 0.917, P = 0.001; OR = 3.168, P < 0.001, respectively]. Individuals with MetS had a lower APOA-I GRS and higher APOB levels after adjustments (OR = 0.870, 6.098, respectively, all P < 0.001). In addition, individuals in the top quintile of the APOA-I genetic score distribution had a lower risk of insulin resistance and MetS after adjustments (OR = 0.761, P = 0.007; OR = 0.637, P < 0.001, respectively). Conclusions In patients with OSA, cumulative effects of APOA-I genetic variations decreased the risk of insulin resistance and MetS, whereas multiple APOB genetic variations had no associations with insulin resistance and MetS.

PAI-1 Concentrations in First-degree Relatives of Patients with Non-insulin-dependent Diabetes: Metabolic and Genetic Associations

1997 ◽  
Vol 77 (02) ◽  
pp. 357-361 ◽  
Author(s):  
Michael W Mansfield ◽  
Max H Stickland ◽  
Peter J Grant
Keyword(s):  
Insulin Resistance ◽  
Promoter Polymorphism ◽  
Activity Levels ◽  
Fasting Insulin ◽  
Genetic Associations ◽  
Additional Mechanism ◽  
First Degree Relatives ◽  
Insulin Dependent ◽  
Niddm Patients ◽  
Pai 1

SummaryAim: To identify whether levels of PAI-1 are elevated in relatives of NIDDM patients and the extent to which they relate to features of insulin resistance and to genotype at a common PAI-1 promoter polymorphism.Results: In 132 first-degree relatives of NIDDM patients and 151 controls PAI-1 activity was higher in relatives 14.4 U/ml than controls U/ml (p <0.0005) with higher body mass index 27.3 v. 24.7 kg/m2 p <0.0005, fasting insulin 9.3 v. 7.6 mU/l p <0.005 and triglyceride v. 1.2 mmol/1 p <0.05. PAI-1 activity levels were higher in men and in smokers and showed a trend to being higher with increasing number of 4G alleles at the PAI-1 promoter polymorphism. After adjustment for age, sex, smoking, BMI and triglyceride levels, PAI-1 levels remained 26% higher in the NIDDM relatives (p = 0.01).Conclusion: In relatives of NIDDM patients PAI-1 levels are elevated, presenting an additional mechanism for their increased cardiovascular risk.

scholarly journals Metabolomic and genetic associations with insulin resistance in pregnancy

Diabetologia ◽  
2020 ◽  
Vol 63 (9) ◽  
pp. 1783-1795 ◽  
Author(s):  
Yu Liu ◽  
◽  
Alan Kuang ◽  
Octavious Talbot ◽  
James R. Bain ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Genetic Associations ◽  
In Pregnancy

scholarly journals Insulin Resistance and Endothelial Dysfunction Constitute a Common Therapeutic Target in Cardiometabolic Disorders

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
A. Janus ◽  
E. Szahidewicz-Krupska ◽  
G. Mazur ◽  
A. Doroszko
Keyword(s):  
Insulin Resistance ◽  
Cardiovascular Disease ◽  
Metabolic Syndrome ◽  
Endothelial Dysfunction ◽  
Metabolic Pathways ◽  
Metabolic Disturbances ◽  
Lipid Disorders ◽  
Cardiometabolic Disorders ◽  
Treatment Of Hypertension ◽  
The Common

Insulin resistance and other risk factors for atherosclerosis, such as hypertension and hypercholesterolemia, promote endothelial dysfunction and lead to development of metabolic syndrome which constitutes an introduction to cardiovascular disease. The insulin resistance and endothelial dysfunction cross talk between each other by numerous metabolic pathways. Hence, targeting one of these pathologies with pleiotropic treatment exerts beneficial effect on another one. Combined and expletive treatment of hypertension, lipid disorders, and insulin resistance with nonpharmacological interventions and conventional pharmacotherapy may inhibit the transformation of metabolic disturbances to fully developed cardiovascular disease. This paper summarises the common therapeutic targets for insulin resistance, endothelial dysfunction, and vascular inflammatory reaction at molecular level and analyses the potential pleiotropic effects of drugs used currently in management of cardiovascular disease, metabolic syndrome, and diabetes.

scholarly journals Mechanisms mediating insulin resistance in transgenic mice overexpressing mouse apolipoprotein A-II

2004 ◽  
Vol 45 (12) ◽  
pp. 2377-2387 ◽  
Author(s):  
Lawrence W. Castellani ◽  
Peter Gargalovic ◽  
Maria Febbraio ◽  
Sarada Charugundla ◽  
Ming-Len Jien ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Transgenic Mice ◽  
Apolipoprotein A

scholarly journals Influence of multiple apolipoprotein A-I and B genetic variations on insulin resistance and metabolic syndrome in obstructive sleep apnea

2020 ◽  
Author(s):  
Li Xinyi ◽  
Fu Zhihui ◽  
Xu Huajun ◽  
Zou Jianyin ◽  
Zhu Huaming ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Genetic Risk Score ◽  
Cumulative Effect ◽  
Genetic Variations ◽  
Score Distribution ◽  
Genetic Score ◽  
Weak Association ◽  
Apolipoprotein A ◽  
Obstructive Sleep

Abstract Background: The relationships between apolipoprotein A-I (APOA-I), apolipoprotein B (APOB) with insulin resistance, metabolic syndrome (MetS) are unclear in OSA. We aimed to evaluate whether the multiple single nucleotide polymorphism (SNP) variants of APOA-I and APOB exert a collaborative effect on insulin resistance and MetS in OSA. Methods: Initially, 12 APOA-I SNPs and 30 APOB SNPs in 5,259 subjects were examined. After strict screening, four APOA-I SNPs and five APOB SNPs in 4,007 participants were included. For each participant, the genetic risk score (GRS) was calculated based on the cumulative effect of multiple genetic variants of APOA-I and APOB. Logistic regression analyses were used to evaluate the relationships between APOA-I/APOB genetic polymorphisms, insulin resistance, and MetS in OSA. Results: Serum APOB levels increased the risk of insulin resistance and MetS adjusting for age, gender and BMI [odds ratio (OR=3.168, P < 0.001; OR=6.098, P < 0.001, respectively]. APOA-I GRS decreased the risk of insulin resistance and MetS after adjustments (OR = 0.917, P = 0.001; OR = 0.870, P < 0.001, respectively). APOB GRS had no association with insulin resistance (OR = 1.364, P =0.610), and had weak association with MetS after adjustments (OR =1.072, P = 0.042). In addition, individuals in the top quintile of the APOA-I genetic score distribution had a lower risk of insulin resistance and MetS after adjustments (OR = 0.761, P = 0.007; OR = 0.637, P < 0.001, respectively). Conclusions: In patients with OSA, cumulative effects of APOA-I genetic variations decreased the risk of insulin resistance and MetS, whereas multiple APOB genetic variations had no associations with insulin resistance and weak association with MetS.

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