PPARD haplotype influences cholesterol metabolism but is no risk factor of Alzheimer's disease

The Contribution of Hippocampal All-Trans Retinoic Acid (ATRA) Deficiency to Alzheimer's Disease: A Narrative Overview of ATRA-Dependent Gene Expression in Post-Mortem Hippocampal Tissue

There is accumulating evidence that vitamin A (VA) deficiency contributes to the pathogenesis and progression of Alzheimer's disease (AD). All-trans retinoic acid (ATRA), a metabolite of VA in the brain, serves distinct roles in the human hippocampus. Agonists of retinoic acid receptors (RAR), including ATRA, promote activation of the non-amyloidogenic pathway by enhancing expression of α-secretases, providing a mechanistic basis for delaying/preventing amyloid beta (Aβ) toxicity. However, whether ATRA is actually deficient in the hippocampi of patients with AD is not clear. Here, using a publicly available human transcriptomic dataset, we evaluated the extent to which ATRA-sensitive genes are dysregulated in hippocampal tissue from post-mortem AD brains, relative to age-matched controls. Consistent with ATRA deficiency, we found significant dysregulation of many ATRA-sensitive genes and significant upregulation of RAR co-repressors, supporting the idea of transcriptional repression of ATRA-mediated signaling. Consistent with oxidative stress and neuroinflammation, Nrf2 and NfkB transcripts were upregulated, respectively. Interestingly, transcriptional targets of Nrf2 were not upregulated, accompanied by upregulation of several histone deacetylases. Overall, our investigation of ATRA-sensitive genes in the human hippocampus bolsters the scientific premise of ATRA depletion in AD and that epigenetic factors should be considered and addressed as part of VA supplementation.

Unraveling the impact of 27-hydroxycholesterol in autoimmune diseases: Exploring promising therapeutic approaches

The role of 27-hydroxycholesterol (27-OHC) in autoimmune diseases has become a subject of intense research in recent years. This oxysterol, derived from cholesterol, has been identified as a significant player in modulating immune responses and inflammation. Its involvement in autoimmune pathogenesis has drawn attention to its potential as a therapeutic target for managing autoimmune disorders effectively. 27-OHC, an oxysterol derived from cholesterol, has emerged as a key player in modulating immune responses and inflammatory processes. It exerts its effects through various mechanisms, including activation of nuclear receptors, interaction with immune cells, and modulation of neuroinflammation. Additionally, 27-OHC has been implicated in the dysregulation of lipid metabolism, neurotoxicity, and blood-brain barrier (BBB) disruption. Understanding the intricate interplay between 27-OHC and autoimmune diseases, particularly neurodegenerative disorders, holds promise for developing targeted therapeutic strategies. Additionally, emerging evidence suggests that 27-OHC may interact with specific receptors and transcription factors, thus influencing gene expression and cellular processes in autoimmune disorders. Understanding the intricate mechanisms by which 27-OHC influences immune dysregulation and tissue damage in autoimmune diseases is crucial for developing targeted therapeutic interventions. Further investigations into the molecular pathways and signaling networks involving 27-OHC are warranted to unravel its full potential as a therapeutic target in autoimmune diseases, thereby offering new avenues for disease intervention and management.

Genetic Moderation of the Association of β-Amyloid With Cognition and MRI Brain Structure in Alzheimer Disease

BACKGROUND AND OBJECTIVES

There is considerable heterogeneity in the association between increasing β-amyloid (Aβ) pathology and early cognitive dysfunction in preclinical Alzheimer disease (AD). At this stage, some individuals show no signs of cognitive dysfunction, while others show clear signs of decline. The factors explaining this heterogeneity are particularly important for understanding progression in AD but remain largely unknown. In this study, we examined an array of genetic variants that may influence the relationships among Aβ, brain structure, and cognitive performance in 2 large cohorts.

METHODS

In 2,953 cognitively unimpaired participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimer disease (A4) study, interactions between genetic variants and 18F-Florbetapir PET standardized uptake value ratio (SUVR) to predict the Preclinical Alzheimer Cognitive Composite (PACC) were assessed. Genetic variants identified in the A4 study were evaluated in the Alzheimer Disease Neuroimaging Initiative (ADNI, N = 527) for their association with longitudinal cognition and brain atrophy in both cognitively unimpaired participants and those with mild cognitive impairment.

RESULTS

In the A4 study, 4 genetic variants significantly moderated the association between Aβ load and cognition. Minor alleles of 3 variants were associated with additional decreases in PACC scores with increasing Aβ SUVR (rs78021285, β = -2.29, SE = 0.40, p FDR = 0.02, nearest gene ARPP21; rs71567499, β = -2.16, SE = 0.38, p FDR = 0.02, nearest gene PPARD; and rs10974405, β = -1.68, SE = 0.29, p FDR = 0.02, nearest gene GLIS3). The minor allele of rs7825645 was associated with less decrease in PACC scores with increasing Aβ SUVR (β = 0.71, SE = 0.13, p FDR = 0.04, nearest gene FGF20). The genetic variant rs76366637, in linkage disequilibrium with rs78021285, was available in both the A4 and ADNI. In the A4, rs76366637 was strongly associated with reduced PACC scores with increasing Aβ SUVR (β = -1.01, SE = 0.21, t = -4.90, p < 0.001). In the ADNI, rs76366637 was associated with accelerated cognitive decline (χ2 = 15.3, p = 0.004) and atrophy over time (χ2 = 26.8, p < 0.001), with increasing Aβ SUVR.

DISCUSSION

Patterns of increased cognitive dysfunction and accelerated atrophy due to specific genetic variation may explain some of the heterogeneity in cognition in preclinical and prodromal AD. The genetic variant near ARPP21 associated with lower cognitive scores in the A4 and accelerated cognitive decline and brain atrophy in the ADNI may help to identify those at the highest risk of accelerated progression of AD.

Discovery and validation of Ferroptosis-related molecular patterns and immune characteristics in Alzheimer's disease

Background

To date, the pathogenesis of Alzheimer's disease is still not fully elucidated. Much evidence suggests that Ferroptosis plays a crucial role in the pathogenesis of AD, but little is known about its molecular immunological mechanisms. Therefore, this study aims to comprehensively analyse and explore the molecular mechanisms and immunological features of Ferroptosis-related genes in the pathogenesis of AD.

Materials and methods

We obtained the brain tissue dataset for AD from the GEO database and downloaded the Ferroptosis-related gene set from FerrDb for analysis. The most relevant Hub genes for AD were obtained using two machine learning algorithms (Least absolute shrinkage and selection operator (LASSO) and multiple support vector machine recursive feature elimination (mSVM-RFE)). The study of the Hub gene was divided into two parts. In the first part, AD patients were genotyped by unsupervised cluster analysis, and the different clusters' immune characteristics were analysed. A PCA approach was used to quantify the FRGscore. In the second part: we elucidate the biological functions involved in the Hub genes and their role in the immune microenvironment by integrating algorithms (GSEA, GSVA and CIBERSORT). Analysis of Hub gene-based drug regulatory networks and mRNA-miRNA-lncRNA regulatory networks using Cytoscape. Hub genes were further analysed using logistic regression models.

Results

Based on two machine learning algorithms, we obtained a total of 10 Hub genes. Unsupervised clustering successfully identified two different clusters, and immune infiltration analysis showed a significantly higher degree of immune infiltration in type A than in type B, indicating that type A may be at the peak of AD neuroinflammation. Secondly, a Hub gene-based Gene-Drug regulatory network and a ceRNA regulatory network were successfully constructed. Finally, a logistic regression algorithm-based AD diagnosis model and Nomogram diagram were developed.

Conclusion

Our study provides new insights into the role of Ferroptosis-related molecular patterns and immune mechanisms in AD, as well as providing a theoretical basis for the addition of diagnostic markers for AD.

Leveraging Genomic Associations in Precision Digital Care for Weight Loss: Cohort Study

BACKGROUND

The COVID-19 pandemic has highlighted the urgency of addressing an epidemic of obesity and associated inflammatory illnesses. Previous studies have demonstrated that interactions between single-nucleotide polymorphisms (SNPs) and lifestyle interventions such as food and exercise may vary metabolic outcomes, contributing to obesity. However, there is a paucity of research relating outcomes from digital therapeutics to the inclusion of genetic data in care interventions.

OBJECTIVE

This study aims to describe and model the weight loss of participants enrolled in a precision digital weight loss program informed by the machine learning analysis of their data, including genomic data. It was hypothesized that weight loss models would exhibit a better fit when incorporating genomic data versus demographic and engagement variables alone.

METHODS

A cohort of 393 participants enrolled in Digbi Health's personalized digital care program for 120 days was analyzed retrospectively. The care protocol used participant data to inform precision coaching by mobile app and personal coach. Linear regression models were fit of weight loss (pounds lost and percentage lost) as a function of demographic and behavioral engagement variables. Genomic-enhanced models were built by adding 197 SNPs from participant genomic data as predictors and refitted using Lasso regression on SNPs for variable selection. Success or failure logistic regression models were also fit with and without genomic data.

RESULTS

Overall, 72.0% (n=283) of the 393 participants in this cohort lost weight, whereas 17.3% (n=68) maintained stable weight. A total of 142 participants lost 5% bodyweight within 120 days. Models described the impact of demographic and clinical factors, behavioral engagement, and genomic risk on weight loss. Incorporating genomic predictors improved the mean squared error of weight loss models (pounds lost and percent) from 70 to 60 and 16 to 13, respectively. The logistic model improved the pseudo R2 value from 0.193 to 0.285. Gender, engagement, and specific SNPs were significantly associated with weight loss. SNPs within genes involved in metabolic pathways processing food and regulating fat storage were associated with weight loss in this cohort: rs17300539_G (insulin resistance and monounsaturated fat metabolism), rs2016520_C (BMI, waist circumference, and cholesterol metabolism), and rs4074995_A (calcium-potassium transport and serum calcium levels). The models described greater average weight loss for participants with more risk alleles. Notably, coaching for dietary modification was personalized to these genetic risks.

CONCLUSIONS

Including genomic information when modeling outcomes of a digital precision weight loss program greatly enhanced the model accuracy. Interpretable weight loss models indicated the efficacy of coaching informed by participants' genomic risk, accompanied by active engagement of participants in their own success. Although large-scale validation is needed, our study preliminarily supports precision dietary interventions for weight loss using genetic risk, with digitally delivered recommendations alongside health coaching to improve intervention efficacy.

CYP46A1 variants influence Alzheimer’s disease risk and brain cholesterol metabolism

Background

Cholesterol 24S-hydroxylase (CYP46) catalyzes the conversion of cholesterol to 24S-hydroxycholesterol, the primary cerebral cholesterol elimination product. Only few gene variations in CYP46 gene (CYP46A1) have been investigated for their relevance as genetic risk factors of Alzheimer’s disease (AD) and results are contradictory.

Methods

We performed a gene variability screening in CYP46A1 and investigated the effect of gene variants on the risk of AD and on CSF levels of cholesterol and 24S-hydroxycholesterol.

Results

Two of the identified 16 SNPs in CYP46A1 influenced AD risk in our study (rs7157609: p = 0.016; rs4900442: p = 0.019). The interaction term of both SNPs was also associated with an increased risk of AD (p = 0.006). Haplotypes including both SNPs were calculated and haplotype G–C was identified to influence the risk of AD (p = 0.005). AD patients and non-demented controls, who were carriers of the G–C haplotype, presented with reduced CSF levels of 24S-hydroxycholesterol (p = 0.001) and cholesterol (p < 0.001).

Conclusion

Our results suggest that CYP46A1 gene variations might act as risk factor for AD via an influence on brain cholesterol metabolism.

Knowledge-Based Neuroendocrine Immunomodulation (NIM) Molecular Network Construction and Its Application

Growing evidence shows that the neuroendocrine immunomodulation (NIM) network plays an important role in maintaining and modulating body function and the homeostasis of the internal environment. The disequilibrium of NIM in the body is closely associated with many diseases. In the present study, we first collected a core dataset of NIM signaling molecules based on our knowledge and obtained 611 NIM signaling molecules. Then, we built a NIM molecular network based on the MetaCore database and analyzed the signaling transduction characteristics of the core network. We found that the endocrine system played a pivotal role in the bridge between the nervous and immune systems and the signaling transduction between the three systems was not homogeneous. Finally, employing the forest algorithm, we identified the molecular hub playing an important role in the pathogenesis of rheumatoid arthritis (RA) and Alzheimer’s disease (AD), based on the NIM molecular network constructed by us. The results showed that GSK3B, SMARCA4, PSMD7, HNF4A, PGR, RXRA, and ESRRA might be the key molecules for RA, while RARA, STAT3, STAT1, and PSMD14 might be the key molecules for AD. The molecular hub may be a potentially druggable target for these two complex diseases based on the literature. This study suggests that the NIM molecular network in this paper combined with the forest algorithm might provide a useful tool for predicting drug targets and understanding the pathogenesis of diseases. Therefore, the NIM molecular network and the corresponding online tool will not only enhance research on complex diseases and system biology, but also promote the communication of valuable clinical experience between modern medicine and Traditional Chinese Medicine (TCM).

A population association study of PPAR δ gene rs2016520 and rs9794 polymorphisms and haplotypes with body mass index and waist circumference in a Chinese population

BACKGROUND

Peroxisome proliferator-activated receptor (PPAR) gene plays an important role in obesity and PPAR δ protein is a potent inhibitor; however, few previous studies have focused on this gene.

AIM

To investigate the association of haplotypes of PPAR δ gene rs2016520 and rs9794 with abnormal weight (BMI ≥ 24 kg/m(2)) and abdominal obesity (WC ≥ 90 cm for males and ≥ 80 cm for females) in a Chinese Han population.

SUBJECTS AND METHODS

In total, 820 subjects (270 men, 550 women) were randomly selected from the PMMJS cohort population and no individuals were related. rs2016520 and rs9794 were detected by TaqMan fluorescence probe. Hardy-Weinberg equilibrium (HWE) was used to detect genotype typing errors by Fisher's exact test. Linkage disequilibrium (LD) between polymorphisms was estimated by using SHEsis. Two PPAR δ SNPs (rs2016520 and rs9794) were analysed by using the logistic regression model.

RESULTS

After adjustment for covariates, the haplotype containing the rs1026520-C and rs9794-C alleles was associated with a statistically significant decreased risk of obesity (OR = 0.64; 95% CI = 0.48-0.84, p = 0.0015). Coincidentally, the haplotype containing the rs1026520-C and rs9794-C alleles was also associated with a statistically decreased risk of abdominal obesity after covariate adjustment (OR = 0.59, 95% CI = 0.45-0.77, p < 0.001).

CONCLUSION

C-C haplotype, constructed from rs2016520 and rs9794 alleles, showed a significant protective effect for both abnormal weight and abdominal obesity.

Role of peroxisome proliferator-activated receptors gene polymorphisms in type 2 diabetes and metabolic syndrome

Metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) are the serious public health problems worldwide. Moreover, it is estimated that MetS patients have about five-fold greater risk of the T2DM development compared with people without the syndrome. Peroxisome proliferator-activated receptors are a subgroup of the nuclear hormone receptor superfamily of ligand-activated transcription factors which play an important role in the pathogenesis of MetS and T2DM. All three members of the peroxisome proliferator-activated receptor (PPAR) nuclear receptor subfamily, PPARα, PPARβ/δ and PPARγ are critical in regulating insulin sensitivity, adipogenesis, lipid metabolism, and blood pressure. Recently, more and more studies indicated that the gene polymorphism of PPARs, such as Leu¹⁶²Val and Val²²⁷Ala of PPARα, +294T > C of PPARβ/δ, Pro¹²Ala and C1431T of PPARγ, are significantly associated with the onset and progressing of MetS and T2DM in different population worldwide. Furthermore, a large body of evidence demonstrated that the glucose metabolism and lipid metabolism were influenced by gene-gene interaction among PPARs genes. However, given the complexity pathogenesis of metabolic disease, it is unlikely that genetic variation of a single locus would provide an adequate explanation of inter-individual differences which results in diverse clinical syndromes. Thus, gene-gene interactions and gene-environment interactions associated with T2DM and MetS need future comprehensive studies.

Integrative and systemic approaches for evaluating PPARβ/δ (PPARD) function

The peroxisome proliferator-activated receptors (PPARs) are a group of nuclear receptors that function as transcription factors regulating the expression of genes involved in cellular differentiation, development, metabolism and also tumorigenesis. Three PPAR isotypes (α, β/δ and γ) have been identified, among which PPARβ/δ is the most difficult to functionally examine due to its tissue-specific diversity in cell fate determination, energy metabolism and housekeeping activities. PPARβ/δ acts both in a ligand-dependent and -independent manner. The specific type of regulation, activation or repression, is determined by many factors, among which the type of ligand, the presence/absence of PPARβ/δ-interacting corepressor or coactivator complexes and PPARβ/δ protein post-translational modifications play major roles. Recently, new global approaches to the study of nuclear receptors have made it possible to evaluate their molecular activity in a more systemic fashion, rather than deeply digging into a single pathway/function. This systemic approach is ideally suited for studying PPARβ/δ, due to its ubiquitous expression in various organs and its overlapping and tissue-specific transcriptomic signatures. The aim of the present review is to present in detail the diversity of PPARβ/δ function, focusing on the different information gained at the systemic level, and describing the global and unbiased approaches that combine a systems view with molecular understanding.

PPARD rs2016520 polymorphism and circulating lipid levels connect with brain diseases in Han Chinese and suggest sex-dependent effects

The PPARD polymorphisms were shown to be associated with circulating lipoprotein metabolism in various diseases. We aimed to check the contribution of PPARD rs2016520 and lipid concentration to the risk of intracerebral hemorrhages (ICH) and brain tumors (BT) in Han Chinese. A total of 864 participants were included in the case-control study. The melting temperature shift (Tm-shift) method was used for rs2016520 genotyping. Under the recessive model, PPARD rs2016520 was shown to be associated with the risk of ICH (P=0.029, odds ratio (OR)=2.72), specifically in males (P=0.045, OR=3.98). Additionally, we also found that the levels of TC and LDL-C were significantly higher in participants with brain diseases than in the controls (TC: P<0.0001; LDL-C: P<0.0001). Significantly higher HDL-C and lower ApoA-I levels were observed in the male patients with brain diseases (HDL-C: P<0.0001; ApoA-I: P=0.008), in contrast of a higher TG level in female ICH (P=0.023). Subsequent interaction analysis between PPARD rs2016520 and lipoprotein metabolism showed that the LDL-C level was positively correlated with ICH in the rs2016520-AA carriers (P<0.0001), but not in the other genotype carriers (AG or GG, P=0.300). Our results showed that PPARD rs2016520 displayed a strong relationship with ICH risk in the male Han Chinese. The TC and LDL-C levels were positively higher in the patients with brain diseases than in the controls. The levels of TG, HDL-C and ApoA-I were shown to affect brain disease in a gender-dependent model. The genotype rs2016520-AA showed significant interaction with the circulating LDL-C levels in ICH.

PPARβ/δ modulates ethanol-induced hepatic effects by decreasing pyridoxal kinase activity

Because of the significant morbidity and lethality caused by alcoholic liver disease (ALD), there remains a need to elucidate the regulatory mechanisms that can be targeted to prevent and treat ALD. Toward this goal, minimally invasive biomarker discovery represents an outstanding approach for these purposes. The mechanisms underlying ALD include hepatic lipid accumulation. As the peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) has been shown to inhibit steatosis, the present study examined the role of PPARβ/δ in ALD coupling metabolomic, biochemical and molecular biological analyses. Wild-type and Pparβ/δ-null mice were fed either a control or 4% ethanol diet and examined after 4-7 months of treatment. Ethanol fed Pparβ/δ-null mice exhibited steatosis after short-term treatment compared to controls, the latter effect appeared to be due to increased activity of sterol regulatory element binding protein 1c (SREBP1c). The wild-type and Pparβ/δ-null mice fed the control diet showed clear differences in their urinary metabolomic profiles. In particular, metabolites associated with arginine and proline metabolism, and glycerolipid metabolism, were markedly different between genotypes suggesting a constitutive role for PPARβ/δ in the metabolism of these amino acids. Interestingly, urinary excretion of taurine was present in ethanol-fed wild-type mice but markedly lower in similarly treated Pparβ/δ-null mice. Evidence suggests that PPARβ/δ modulates pyridoxal kinase activity by altering Km, consistent with the observed decreased in urinary taurine excretion. These data collectively suggest that PPARβ/δ prevents ethanol-induced hepatic effects by inhibiting hepatic lipogenesis, modulation of amino acid metabolism, and altering pyridoxal kinase activity.

The peroxisome proliferator-activated receptor delta +294T > C polymorphism and alcohol consumption on serum lipid levels

Background

The single nucleotide polymorphism (SNP) of peroxisome proliferator-activated receptor delta (PPARD) gene affects serum lipid profiles, but to what extent alcohol consumption interferes with this association remains unknown. The present study was undertaken to compare the association of PPARD +294T > C (rs2016520) polymorphism and serum lipid levels in the nondrinkers and drinkers.

Methods

A total of 685 unrelated nondrinkers and 497 drinkers aged 15-82 were randomly selected from our previous stratified randomized cluster samples. Genotyping of the PPARD +294T > C was performed by polymerase chain reaction and restriction fragment length polymorphism. Interactions of the PPARD +294T > C genotypes and alcohol consumption on serum lipid levels were detected by using a factorial regression analysis after controlling for potential confounders.

Results

The levels of triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), apolipoprotein (Apo) A1, and the ratio of ApoA1 to ApoB were higher in drinkers than in nondrinkers (P < 0.05-0.001). There were no significant differences in the levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and ApoB between the two groups (P > 0.05 for all). The frequencies of TT, TC and CC genotypes were 56.0%, 36.4% and 7.6% in nondrinkers, and 57.2%, 38.0% and 4.8% in drinkers (P > 0.05); respectively. The frequencies of T and C alleles were 74.2% and 25.8% in nondrinkers, and 76.2% and 23.8% in drinkers (P > 0.05); respectively. There was also no significant difference in the genotypic and allelic frequencies between males and females in both groups (P > 0.05 for all). The levels of TC in nondrinkers were different among the three genotypes (P = 0.01), the C allele carriers had higher serum TC levels than the C allele noncarriers. The levels of all seven lipid traits in drinkers were not different among the three genotypes (P > 0.05 for all). The interactions of PPARD +294T > C genotypes and alcohol consumption on serum lipid levels were not detected in the drinkers (P >0.05 for all). Multiple linear regression analysis showed that serum TC, HDL-C, LDL-C, ApoA1, and ApoB levels were correlated with genotypes in drinkers but not in nondrinkers (P < 0.05-0.01).

Conclusions

These results suggest that the great majority of our study populations are beneficial from alcohol consumption. But there is no interaction between the PPARD +294T > C genotypes and alcohol consumption on serum lipid levels in the drinkers.

Peroxisome proliferator-activated receptor delta +294T > C polymorphism and serum lipid levels in the Guangxi Bai Ku Yao and Han populations

BACKGROUND

The association of peroxisome proliferator-activated receptor delta (PPARD) +294T > C polymorphism and serum lipid levels is inconsistent in several previous studies. Bai Ku Yao is an isolated subgroup of the Yao minority in China. The present study was undertaken to detect the association of PPARD +294T > C (rs2016520) polymorphism and several environmental factors with serum lipid levels in the Guangxi Bai Ku Yao and Han populations.

METHODS

A total of 609 subjects of Bai Ku Yao and 573 participants of Han Chinese were randomly selected from our previous stratified randomized cluster samples. Genotyping of the PPARD +294T > C polymorphism was performed by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and then confirmed by direct sequencing.

RESULTS

The levels of serum total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), apolipoprotein (Apo) AI and ApoB were lower in Bai Ku Yao than in Han (P < 0.001 for all). The frequency of T and C alleles was 77.50% and 22.50% in Bai Ku Yao, and 72.43% and 27.57% in Han (P < 0.01); respectively. The frequency of TT, TC and CC genotypes was 60.59%, 33.83% and 5.53% in Bai Ku Yao, and 52.18%, 40.50% and 7.32% in Han (P < 0.05); respectively. The subjects with CC genotype in Bai Ku Yao had higher serum LDL-C and ApoB levels and lower the ratio of ApoAI to ApoB than the subjects with TT and TC genotypes in females but not in males. The C allele carriers in Han had higher serum TC levels in males (P < 0.01) and ApoB levels in females (P < 0.05) than the C allele noncarriers. Serum TC and ApoB levels were correlated with genotypes in Han (P < 0.05 for each) but not in Bai Ku Yao. Serum lipid parameters were also correlated with sex, age, body mass index, alcohol consumption, cigarette smoking, and blood pressure in both ethnic groups.

CONCLUSIONS

These results suggest that the association of PPARD +294T > C polymorphism and serum lipid levels is different between the Bai Ku Yao and Han populations. The discrepancy between the two ethnic groups might partly result from different PPARD +294T > C polymorphism or PPARD gene-environmental interactions.

Peroxisome proliferator-activated receptors, metabolic syndrome and cardiovascular disease

Metabolic syndrome (MetS) is a constellation of risk factors including insulin resistance, central obesity, dyslipidemia and hypertension that markedly increase the risk of Type 2 diabetes (T2DM) and cardiovascular disease (CVD). The peroxisome proliferators-activated receptor (PPAR) isotypes, PPARα, PPARδ/ß and PPARγ are ligand-activated nuclear transcription factors, which modulate the expression of an array of genes that play a central role in regulating glucose, lipid and cholesterol metabolism, where imbalance can lead to obesity, T2DM and CVD. They are also drug targets, and currently, PPARα (fibrates) and PPARγ (thiazolodinediones) agonists are in clinical use for treating dyslipidemia and T2DM, respectively. These metabolic characteristics of the PPARs, coupled with their involvement in metabolic diseases, mean extensive efforts are underway worldwide to develop new and efficacious PPAR-based therapies for the treatment of additional maladies associated with the MetS. This article presents an overview of the functional characteristics of three PPAR isotypes, discusses recent advances in our understanding of the diverse biological actions of PPARs, particularly in the vascular system, and summarizes the developmental status of new single, dual, pan (multiple) and partial PPAR agonists for the clinical management of key components of MetS, T2DM and CVD. It also summarizes the clinical outcomes from various clinical trials aimed at evaluating the atheroprotective actions of currently used fibrates and thiazolodinediones.

Genetic study between SIRT1, PPARD, PGC-1alpha genes and Alzheimer's disease

Single nucleotide polymorphisms (SNPs) in three diabetes-related genes (SIRT1, PPARD, PGC-1alpha) were investigated with a case-control approach. To examine the genetic association of those genes with Alzheimer's disease (AD) risk, we used the TaqMan technique to genotype five SNP sites for SIRT1, six for PPARD and eight for the PGC-1alpha gene, in 326 Finnish AD cases and 463 controls and conducted a single allele and genotypic distribution comparison as well as estimated haplotype frequencies between cases and controls. No significant differences in AD risk were found in single SNP and haplotype analyses for any of the three genes between 326 cases and 463 controls. However, in a subgroup of women older than 65 years, the frequencies of three SNPs in the SIRT1 gene were significantly different between AD and controls. We conclude that there is no real association with SNPs available in the present study between SIRT1, PPARD or PGC-1alpha genes and AD risk in the Finnish population.

Single gene contributions: genetic variants of peroxisome proliferator-activated receptor (isoforms alpha, beta/delta and gamma) and mechanisms of dyslipidemias

PURPOSE OF REVIEW

Polymorphisms in peroxisome proliferator-activated receptor isoforms may be among the most important single-gene contributors to dyslipidemias, insulin resistance, and maturity-onset diabetes.

RECENT FINDINGS

Familial partial lipodystrophy is a rare but characteristic phenotype associated with carriers of peroxisome proliferator-activated receptor-gamma missense mutations. Mutant receptors are transcriptionally defective, exhibit aberrant affinity for co-regulator molecules, and can exert dominant-negative or haplo-insufficiency effects on normal peroxisome proliferator-activated receptor-gamma function. The P12A variant of isoform gamma is estimated to reduce diabetes risk by 19% in many populations, and has a large attributable risk because of high prevalence of the normal allele. Variants L162V and V227A of isoform alpha (common in white and Oriental populations, respectively) are associated with sexually dimorphic perturbations of lipid metabolism and cardiovascular risk. Polymorphisms in isoforms alpha and beta/delta are reported to influence lipid and glucose utilization. Apart from lipodystrophic syndromes, metabolic and cardiovascular risk in peroxisome proliferator-activated receptor variants is apparently modulated by dietary and exercise interventions, and interactions with polymorphisms in other genetic loci.

SUMMARY

Polymorphisms in peroxisome proliferator-activated receptors are critical susceptibility risk factors for dyslipidemias and diabetes. They provide attractive targets for gene-environment interventions to reduce the burden of metabolic disease.

Association study of cholesterol-related genes in Alzheimer's disease

Alzheimer's disease (AD) is a genetically complex disorder, and several genes related to cholesterol metabolism have been reported to contribute to AD risk. To identify further AD susceptibility genes, we have screened genes that map to chromosomal regions with high logarithm of the odds scores for AD in full genome scans and are related to cholesterol metabolism. In a European screening sample of 115 sporadic AD patients and 191 healthy control subjects, we analyzed single nucleotide polymorphisms in 28 cholesterol-related genes for association with AD. The genes HMGCS2, FDPS, RAFTLIN, ACAD8, NPC2, and ABCG1 were associated with AD at a significance level of P < or = 0.05 in this sample. Replication trials in five independent European samples detected associations of variants within HMGCS2, FDPS, NPC2, or ABCG1 with AD in some samples (P = 0.05 to P = 0.005). We did not identify a marker that was significantly associated with AD in the pooled sample (n = 2864). Stratification of this sample revealed an APOE-dependent association of HMGCS2 with AD (P = 0.004). We conclude that genetic variants investigated in this study may be associated with a moderate modification of the risk for AD in some samples.