Large Human Cohorts Research Articles

Low levels of a natural IgM antibody are associated with vein graft stenosis and failure

All humans have natural, protective antibodies directed against phosphorylcholine (PC) epitopes, a common inflammatory danger signal appearing at sites of cell injury, oxidative stress, and on bacterial capsules. In large human cohorts, low levels of anti-PC IgM were associated with a significantly increased risk of stroke or myocardial infarction. However, it is not known if these antibodies protect against the premature closure of arterial reconstructions. A prospective, observational study of patients undergoing elective, infrainguinal, autogenous vein bypasses for atherosclerotic occlusive disease of the legs was conducted. Clinical data were recorded prospectively, and preoperative levels of anti-PC IgM measured with the CVDefine kit from Athera Biotechnologies (Solna, Sweden). The principal clinical end point was the loss of primary patency (loss of graft flow, or any intervention for stenosis). Patients were followed regularly by duplex ultrasound at 1, 3, 6, 12, 18 months, and yearly thereafter. Fifty-six patients were studied, for an average of 1.3 years. Indications for surgery were claudication (33.9%), ischemic rest pain (17.9%), and ischemia with ulceration or gangrene (48.2%). Seventeen (30.4%) patients experienced loss of primary patency (10 graft occlusions, seven surgical or endovascular revisions of graft stenoses). Kaplan-Meier survival analysis showed that the quartile of patients with the lowest anti-PC IgM levels had significantly worse primary graft patency (log-rank test, P = .0085). Uni- and multivariate Cox proportional hazards analysis revealed that the preoperative anti-PC IgM level was an important predictor of graft failure. Patients with IgM values in the lowest quartile had a 3.6-fold increased risk of graft failure (95% confidence interval: 1.1-12.1), even after accounting for other significant clinical or technical factors such as indication for surgery, site of distal anastomosis, or vein graft diameter. A naturally occurring IgM antibody directed against the proinflammatory epitope PC may be protective against vein graft stenosis and failure, through anti-inflammatory mechanisms. Measurement of this antibody may be a useful prognostic indicator, although larger studies of more diverse populations will be needed to confirm these results. The biological actions of anti-PC IgM suggest it may be useful in developing immunotherapies to improve bypass longevity.

Impact of the Environment on the Skeleton: Is it Modulated by Genetic Factors?

The etiology of skeletal disease is driven by genetic and environmental factors. Genome-wide association studies (GWAS) of osteoporotic phenotypes have identified novel candidate genes, but have only uncovered a small proportion of the trait variance explained. This "missing heritability" is caused by several factors, including the failure to consider gene-by-environmental (G*E) interactions. Some G*E interactions have been investigated, but new approaches to integrate environmental data into genomic studies are needed. Advances in genotyping and meta-analysis techniques now allow combining genotype data from multiple studies, but the measurement of key environmental factors in large human cohorts still lags behind, as do the statistical tools needed to incorporate these measures in genome-wide association meta-studies. This review focuses on discussing ways to enhance G*E interaction studies in humans and how the use of rodent models can inform genetic studies. Understanding G*E interactions will provide opportunities to effectively target intervention strategies for individualized therapy.

A Roadmap to the Human Virome

Low-cost DNA sequencing has greatly democratized genomics, especially for the typically very small genomes of viruses [1]–[3]. The recent acceleration in human virus discovery by metagenomics indicates that many viruses escaped prior detection due to limitations of preexisting technologies. It is now conceivable that all viral species commonly infecting human (i.e., the human virome) will soon be determined. As the value of the human genome and microbiome has become widely recognized, providing crucial reference genomes and opening unanticipated avenues of research, the genetic characterization of the human virome also holds great promises [4]. The human microbiome project, focusing largely on single bacterial cells and metagenomic sequencing of total DNA from feces and other human sites, is unlikely to detect RNA viruses. The generally minuscule size of viral genomes relative to those of their bacterial or eukaryotic hosts also weighs against their easy detection in metagenomic approaches. Viral discovery can be greatly facilitated by simple filtration to enrich the smaller viral particles and by removal of contaminating bacterial and human nucleic acids using nuclease digestion that leave viral nucleic acids protected within their virion shells (Figure 1) [5]. Density gradient ultra-centrifugation has also been used to enrich viral particles. Figure 1 Schematic steps for determination of human virome and its impact on health, including biological samples and data acquisition, genetic analysis, and epidemiology of viral infections. Knowledge of the human virome will allow the design of sensitive and specific tests to all human viruses using “virochip” microarrays [6] or multiplexed PCR assays (Figure 1). Provided samples from large enough human cohorts are analyzed, it will be possible to determine viral prevalence, likely transmission routes, and most crucially disease association. The development of vaccines and antivirals can then be targeted to the viruses with the largest public health impacts in different geographic regions. Deciphering the complete human virome will therefore improve our understanding, prevention, and treatment of currently unexplained diseases involving viral pathogens, as well as provide insights into the evolution of viral families and cross-species viral transmissions. Despite the rapid progress being made toward deciphering the human virome, several roadblocks remain to its full characterization and utilization. Below is an abbreviated list of these problems and possible solutions.

Rapid variance components–based method for whole-genome association analysis

The variance component tests used in genome-wide association studies (GWAS) including large sample sizes become computationally exhaustive when the number of genetic markers is over a few hundred thousand. We present an extremely fast variance components-based two-step method, GRAMMAR-Gamma, developed as an analytical approximation within a framework of the score test approach. Using simulated and real human GWAS data sets, we show that this method provides unbiased estimates of the SNP effect and has a power close to that of the likelihood ratio test-based method. The computational complexity of our method is close to its theoretical minimum, that is, to the complexity of the analysis that ignores genetic structure. The running time of our method linearly depends on sample size, whereas this dependency is quadratic for other existing methods. Simulations suggest that GRAMMAR-Gamma may be used for association testing in whole-genome resequencing studies of large human cohorts.

Abstract 5256: Gender bias in rat models of colorectal cancer is owing to male hormone promotion, not female hormone protection

Abstract Several large human colonoscopy screening cohort studies have found a significant sex and age-specific prevalence of advanced adenomas and colorectal cancer in males, with females showing a delayed onset and decreased incidence of advanced lesions. It has been postulated that women are protected from colorectal cancer owing to a protective effect of estrogen and progesterone, or that males are exposed to higher levels of environmental toxins. We find in both a genetic and a carcinogen-induced model of colorectal cancer in rats that male hormones are responsible for the male-specific enhancement of colon cancer. We have reported that the Polyposis in the rat colon (Pirc) rat shows a strong gender bias, with females having a later onset and reduced tumor burden compared to males. We have next investigated the role of hormones through ovariectomy and hormone replacement in female rats. F344-Pirc rat litters were divided and either underwent surgical ovariectomy or sham ovariectomy between 35 and 40 days of age. At the time of surgery, females received subcutaneous slow release (90 day) pellets with the following treatments: placebo; 17-beta estradiol (E2); medroxypregesterone (MPA); or a combination of E2 and MPA, renewed after 90 days, and sacrificed 180 days post ovariectomy. The controls were cohorts of females that did not receive surgical treatment (n=10), and sham ovariectomized females (n=10). Females that underwent ovariectomy and received either E2 (n=10) or the combination of E2 and MPA (n=10) had reduced body weight and were observed to be much leaner than animals treated with MPA alone (n=10, p=0.006) or placebo (n=8, p=0.005). Importantly, tumor multiplicities did not significantly differ among all female groups, but were significantly lower than those observed in intact males (n=32, mean 39.4, p=4.7e-14). We postulated that the difference of tumor susceptibility between sexes is due to the effect of male hormones. At weaning (30-35 days) half of the F344-Pirc males underwent orchidectomy. Males that underwent castration (n=16) had a significantly lower tumor multiplicity (mean=16.9) compared to all other males (n=32, mean= 39.4, p=1.3e-6). Males that underwent castration were indisguishable from all Pirc female cohorts, treated or not, strongly suggesting that male gonadal hormones are the significant hormones controlling the multiplicity of colonic adenomas. To determine if this response was specific to our genetic model, cohorts of F344 male rats either underwent orchidectomy or sham operation, and were then treated with the carcinogen azoxymethane. The orchidectomized cohort had a significantly lower number of aberrant crypt foci compared to the sham treated males (p=0.01). We are testing, through DHT replacement in the Pirc rat, whether testosterone is directly promoting the earlier onset and increased severity of colorectal cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5256. doi:1538-7445.AM2012-5256

Transcript-Specific Associations of SLC12A5 (KCC2) in Human Prefrontal Cortex with Development, Schizophrenia, and Affective Disorders

The neuron-specific K(+)-Cl(-) cotransporter SLC12A5, also known as KCC2, helps mediate the electrophysiological effects of GABA. The pattern of KCC2 expression during early brain development suggests that its upregulation drives the postsynaptic switch of GABA from excitation to inhibition. We previously found decreased expression of full-length KCC2 in the postmortem hippocampus of patients with schizophrenia, but not in the dorsolateral prefrontal cortex (DLPFC). Using PCR and rapid amplification of cDNA ends, we discovered several previously unrecognized alternative KCC2 transcripts in both human adult and fetal brain in addition to the previously identified full-length (NM_020708.3) and truncated (AK098371) transcripts. We measured the expression levels of four relatively abundant truncated splice variants, including three novel transcripts (ΔEXON6, EXON2B, and EXON6B) and one previously described transcript (AK098371), in a large human cohort of nonpsychiatric controls across the lifespan, and in patients with schizophrenia and affective disorders. In SH-SY5Y cell lines, these transcripts were translated into proteins and expressed at their predicted sizes. Expression of the EXON6B transcript is increased in the DLPFC of patients with schizophrenia (p = 0.03) but decreased in patients with major depression (p = 0.04). The expression of AK098371 is associated with a GAD1 single nucleotide polymorphism (rs3749034) that previously has been associated with GAD67 expression and risk for schizophrenia. Our data confirm the developmental regulation of KCC2 expression, and provide evidence that KCC2 transcripts are differentially expressed in schizophrenia and affective disorders. Alternate transcripts from KCC2 may participate in the abnormal GABA signaling in the DLPFC associated with schizophrenia.

Automated Systems.

Automated Systems.

AluScan: a method for genome-wide scanning of sequence and structure variations in the human genome

BackgroundTo complement next-generation sequencing technologies, there is a pressing need for efficient pre-sequencing capture methods with reduced costs and DNA requirement. The Alu family of short interspersed nucleotide elements is the most abundant type of transposable elements in the human genome and a recognized source of genome instability. With over one million Alu elements distributed throughout the genome, they are well positioned to facilitate genome-wide sequence amplification and capture of regions likely to harbor genetic variation hotspots of biological relevance.ResultsHere we report on the use of inter-Alu PCR with an enhanced range of amplicons in conjunction with next-generation sequencing to generate an Alu-anchored scan, or 'AluScan', of DNA sequences between Alu transposons, where Alu consensus sequence-based 'H-type' PCR primers that elongate outward from the head of an Alu element are combined with 'T-type' primers elongating from the poly-A containing tail to achieve huge amplicon range. To illustrate the method, glioma DNA was compared with white blood cell control DNA of the same patient by means of AluScan. The over 10 Mb sequences obtained, derived from more than 8,000 genes spread over all the chromosomes, revealed a highly reproducible capture of genomic sequences enriched in genic sequences and cancer candidate gene regions. Requiring only sub-micrograms of sample DNA, the power of AluScan as a discovery tool for genetic variations was demonstrated by the identification of 357 instances of loss of heterozygosity, 341 somatic indels, 274 somatic SNVs, and seven potential somatic SNV hotspots between control and glioma DNA.ConclusionsAluScan, implemented with just a small number of H-type and T-type inter-Alu PCR primers, provides an effective capture of a diversity of genome-wide sequences for analysis. The method, by enabling an examination of gene-enriched regions containing exons, introns, and intergenic sequences with modest capture and sequencing costs, computation workload and DNA sample requirement is particularly well suited for accelerating the discovery of somatic mutations, as well as analysis of disease-predisposing germline polymorphisms, by making possible the comparative genome-wide scanning of DNA sequences from large human cohorts.

Identification of biomarkers for tuberculosis disease using a novel dual-color RT–MLPA assay

Owing to our lack of understanding of the factors that constitute protective immunity during natural infection with Mycobacterium tuberculosis (Mtb), there is an urgent need to identify host biomarkers that predict long-term outcome of infection in the absence of therapy. Moreover, the identification of host biomarkers that predict (in)adequate response to tuberculosis (TB) treatment would similarly be a major step forward. To identify/monitor multi-component host biomarker signatures at the transcriptomic level in large human cohort studies, we have developed and validated a dual-color reverse-transcriptase multiplex ligation-dependent probe amplification (dcRT-MLPA) method, permitting rapid and accurate expression profiling of as many as 60-80 transcripts in a single reaction. dcRT-MLPA is sensitive, highly reproducible, high-throughput, has an extensive dynamic range and is as quantitative as QPCR. We have used dcRT-MLPA to characterize the human immune response to Mtb in several cohort studies in two genetically and geographically diverse populations. A biomarker signature was identified that is strongly associated with active TB disease, and was profoundly distinct from that associated with treated TB disease, latent infection or uninfected controls, demonstrating the discriminating power of our biomarker signature. Identified biomarkers included apoptosis-related genes and T-cell/B-cell markers, suggesting important contributions of adaptive immunity to TB pathogenesis.

Molecular genetic studies of gene identification for sarcopenia

Sarcopenia, which is characterized by a progressive decrease of skeletal muscle mass and function with aging, is closely related to several common diseases (such as cardiovascular and airway diseases) and functional impairment/disability. Strong genetic determination has been reported for muscle mass and muscle strength, two most commonly recognized and studied risk phenotypes for sarcopenia, with heritability ranging from 30 to 85% for muscle strength and 45-90% for muscle mass. Sarcopenia has been the subject of increasing genetic research over the past decade. This review is designed to comprehensively summarize the most important and representative molecular genetic studies designed to identify genetic factors associated with sarcopenia. We have methodically reviewed whole-genome linkage studies in humans, quantitative trait loci mapping in animal models, candidate gene association studies, newly reported genome-wide association studies, DNA microarrays and microRNA studies of sarcopenia or related skeletal muscle phenotypes. The major results of each study are tabulated for easy comparison and reference. The findings of representative studies are discussed with respect to their influence on our present understanding of the genetics of sarcopenia. This is a comprehensive review of molecular genetic studies of gene identification for sarcopenia, and an overarching theme for this review is that the currently accumulating results are tentative and occasionally inconsistent and should be interpreted with caution pending further investigation. Consequently, this overview should enhance recognition of the need to validate/replicate the genetic variants underlying sarcopenia in large human cohorts and animal. We believe that further progress in understanding the genetic etiology of sarcopenia will provide valuable insights into important fundamental biological mechanisms underlying muscle physiology that will ultimately lead to improved ability to recognize individuals at risk for developing sarcopenia and our ability to treat this debilitating condition.

Alterations of lipid metabolism in Wilson disease

IntroductionWilson disease (WD) is an inherited disorder of human copper metabolism, characterised by accumulation of copper predominantly in the liver and brain, leading to severe hepatic and neurological disease. Interesting findings in animal models of WD (Atp7b-/- and LEC rats) showed altered lipid metabolism with a decrease in the amount of triglycerides and cholesterol in the serum. However, serum lipid profile has not been investigated in large human WD patient cohorts to date.Patients and MethodsThis cohort study involved 251 patients examined at the Heidelberg and Dresden (Germany) University Hospitals. Patients were analysed on routine follow-up examinations for serum lipid profile, including triglycerides, cholesterol, high density lipoprotein (HDL) and low density lipoprotein (LDL). Data on these parameters at time of diagnosis were retrieved by chart review where available. For statistical testing, patients were subgrouped by sex, manifestation (hepatic, neurological, mixed and asymptomatic) and treatment (D-penicillamine, trientine, zinc or combination).ResultsA significant difference in total serum cholesterol was found in patients with hepatic symptoms, which diminished under therapy. No alterations were observed for HDL, LDL and triglycerides.ConclusionContradictory to previous reports using WD animal models (Atp7b-/- and LEC rats), the most obvious alteration in our cohort was a lower serum cholesterol level in hepatic-affected patients, which might be related to liver injury. Our data suggested unimpaired cholesterol metabolism in Wilson disease under therapy, independent of the applied medical treatment.

Dietary cystine level affects metabolic rate and glycaemic control in adult mice

Plasma total cysteine (tCys) is strongly and independently associated with obesity in large human cohorts, but whether the association is causal is unknown. Dietary cyst(e)ine increases weight gain in some rodent models. We investigated the body composition, metabolic rate and metabolic phenotype of mature C3H/HeH mice assigned to low-cystine (LC) or high-cystine (HC) diets for 12 weeks.Compared to LC mice, HC mice gained more weight (P=.004 for 12-week weight gain %), with increased fat mass and lean mass, and lowered O2 consumption and CO2 production by calorimetry. The HC mice had 30% increase in intestinal fat/body weight % (P=.003) and ∼twofold elevated hepatic triglycerides (P=.046), with increased expression of hepatic lipogenic factors, peroxisome proliferator-activated receptor-γ and sterol regulatory element binding protein-1. Gene expression of both basal and catecholamine-stimulated lipolytic enzymes, adipose triglyceride lipase and hormone-sensitive lipase was inhibited in HC mice adipose tissue. The HC mice also had elevated fasting glucose (7.0 vs. 4.5 mmol/L, P<.001) and a greater area under the curve (P<.001) in intraperitoneal glucose tolerance tests, with enhanced expression of the negative regulator of insulin signaling, protein tyrosine phosphatase-1B, in liver and adipose tissue.Overall, high cystine intake promotes adiposity and an adverse metabolic phenotype in mice, indicating that the positive association of plasma tCys with obesity in humans may be causal.

Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data

BackgroundWith the advent of high-throughput targeted metabolic profiling techniques, the question of how to interpret and analyze the resulting vast amount of data becomes more and more important. In this work we address the reconstruction of metabolic reactions from cross-sectional metabolomics data, that is without the requirement for time-resolved measurements or specific system perturbations. Previous studies in this area mainly focused on Pearson correlation coefficients, which however are generally incapable of distinguishing between direct and indirect metabolic interactions.ResultsIn our new approach we propose the application of a Gaussian graphical model (GGM), an undirected probabilistic graphical model estimating the conditional dependence between variables. GGMs are based on partial correlation coefficients, that is pairwise Pearson correlation coefficients conditioned against the correlation with all other metabolites. We first demonstrate the general validity of the method and its advantages over regular correlation networks with computer-simulated reaction systems. Then we estimate a GGM on data from a large human population cohort, covering 1020 fasting blood serum samples with 151 quantified metabolites. The GGM is much sparser than the correlation network, shows a modular structure with respect to metabolite classes, and is stable to the choice of samples in the data set. On the example of human fatty acid metabolism, we demonstrate for the first time that high partial correlation coefficients generally correspond to known metabolic reactions. This feature is evaluated both manually by investigating specific pairs of high-scoring metabolites, and then systematically on a literature-curated model of fatty acid synthesis and degradation. Our method detects many known reactions along with possibly novel pathway interactions, representing candidates for further experimental examination.ConclusionsIn summary, we demonstrate strong signatures of intracellular pathways in blood serum data, and provide a valuable tool for the unbiased reconstruction of metabolic reactions from large-scale metabolomics data sets.

Abstract P3-10-23: Caveolin 1 and Patient Outcomes in Breast Cancer

Abstract Introduction: Caveolin 1 (Cav1) protein is a structural component of caveolae in cell membranes and is also present in the cell cytoplasm, nucleus and extracellular milieu. It regulates multiple cellular processes and has been reported to both positively and negatively effect tumour progression. In normal and malignant breast tissue Cav1 is immunohistochemically expressed in myoepithelial and stromal cells but rarely in luminal epithelial or breast cancer cells. Recent reports have correlated Cav1 expression in the stromal tumour microenvironment with lower tumor stage, grade and improved prognosis. This suggests a separate role for Cav 1 in influencing tumour behaviour by regulating the tumour microenvironment. Our aim was to further investigate the role of Cav1 in breast cancer by for the first time analysing its expression by reverse phase protein array(RPPA). Methods: We examined expression levels of Cav1 in 52 breast cancer cell lines and a large human early breast cancer cohort(n=712) with cancer cells composing 70% of the macrodissected breast cancer specimens used. Data was recorded when available for each case on standard clinical, pathological and survival endpoints. We examined the effect of Cav1 expression on tumour biology and patient survival. Results: High levels of Cav1 expression in breast cancer cell lines was strongly correlated with a TN phenotype (P&amp;lt;0.001). Cav 1 expression was more strongly associated with the stromal subtype rather than basal subtype of TN cell lines (p=0.02). In contrast, in human tumour tissue high levels of Cav1 correlated with the hormone receptor positive(ER) phenotype. There was also an association between Cav 1 expression and lower grade (P&amp;lt;0.001), lower T stage (P&amp;lt;0.001) and lower N stage (P&amp;lt;0.001). Cav 1 was significantly associated with improved relapse-free (RFS) and overall survival (OS) in the human cohort. On multivariate(MV) analysis Cav1 was associated with OS(HR 0.91/95% CI 0.82-1/p=0.05) but not RFS. In the subset of ER patients who only received adjuvant tamoxifen (n=199) Cav1 was also significantly associated with improved RFS and OS. MV analysis again showed this correlation to remain for OS (HR 0.81/95% CI 0.65-1/p=0.05) but not for RFS. In the TN subset (n=161) Cav1 expression did not have any survival impact. Discussion: Our results show different expression patterns of Cav1 in vitro and in vivo. TN tumors are thought to originate from the myoepithelial or stromal component of breast tissue which may explain the high levels of Cav1 in this subgroup of breast cancer cell lines. On the other hand, human tumour tissue showed an association between high Cav1 levels and ER tumours. Analysis of these macrodissected samples likely included stromal tissue surrounding the epithelial tumour cells which may explain this discrepancy. Our data also show a correlation between high in vivo levels of Cav1 and less aggressive tumours with improved prognosis. On MV analysis Cav1 was an independent predictor of outcome in the whole cohort and in the ER subset treated with adjuvant tamoxifen only. Expression of stromal Cav1 measured by RPPA may again partly explain these findings. Further analysis with fully microdissected human breast tissue and immunohistochemical analysis of both stromal and cancer cell Cav1 expression is planned. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P3-10-23.

Evaluation of Fasting State-/Oral Glucose Tolerance Test-Derived Measures of Insulin Release for the Detection of Genetically Impaired β-Cell Function

BackgroundTo date, fasting state- and different oral glucose tolerance test (OGTT)-derived measures are used to estimate insulin release with reasonable effort in large human cohorts required, e.g., for genetic studies. Here, we evaluated twelve common (or recently introduced) fasting state-/OGTT-derived indices for their suitability to detect genetically determined β-cell dysfunction.Methodology/Principal FindingsA cohort of 1364 White European individuals at increased risk for type 2 diabetes was characterized by OGTT with glucose, insulin, and C-peptide measurements and genotyped for single nucleotide polymorphisms (SNPs) known to affect glucose- and incretin-stimulated insulin secretion. One fasting state- and eleven OGTT-derived indices were calculated and statistically evaluated. After adjustment for confounding variables, all tested SNPs were significantly associated with at least two insulin secretion measures (p≤0.05). The indices were ranked according to their associations' statistical power, and the ranks an index obtained for its associations with all the tested SNPs (or a subset) were summed up resulting in a final ranking. This approach revealed area under the curve (AUC)Insulin(0-30)/AUCGlucose(0-30) as the best-ranked index to detect SNP-dependent differences in insulin release. Moreover, AUCInsulin(0-30)/AUCGlucose(0-30), corrected insulin response (CIR), AUCC-Peptide(0-30)/AUCGlucose(0-30), AUCC-Peptide(0-120)/AUCGlucose(0-120), two different formulas for the incremental insulin response from 0–30 min, i.e., the insulinogenic indices (IGI)2 and IGI1, and insulin 30 min were significantly higher-ranked than homeostasis model assessment of β-cell function (HOMA-B; p<0.05). AUCC-Peptide(0-120)/AUCGlucose(0-120) was best-ranked for the detection of SNPs involved in incretin-stimulated insulin secretion. In all analyses, HOMA-β displayed the highest rank sums and, thus, scored last.Conclusions/SignificanceWith AUCInsulin(0-30)/AUCGlucose(0-30), CIR, AUCC-Peptide(0-30)/AUCGlucose(0-30), AUCC-Peptide(0-120)/AUCGlucose(0-120), IGI2, IGI1, and insulin 30 min, dynamic measures of insulin secretion based on early insulin and C-peptide responses to oral glucose represent measures which are more appropriate to assess genetically determined β-cell dysfunction than fasting measures, i.e., HOMA-B. Genes predominantly influencing the incretin axis may possibly be best detected by AUCC-Peptide(0-120)/AUCGlucose(0-120).

Understanding the Extent and Sources of Variation in Gut Microbiota Studies; a Prerequisite for Establishing Associations with Disease

Humans harbor distinct commensal microbiota at various anatomic sites. There has been renewed interest in the contributions of microbiota activities to human health and disease. The microbiota of the gut is the most complex of all anatomic sites in terms of total numbers of bacteria that interact closely with the mucosal immune system and contribute various functions to host physiology. Especially in the proximal large intestine a diverse microbiota ferments complex substrates such as dietary fiber and host mucins, but also metabolizes bile acids and phytoestrogens that reach the large intestine. It is now well established that microbiota composition differs between but over time also within individuals. However, a thorough understanding of the sources of variations in microbiota composition, which is an important requirement for large population based microbiota studies is lacking. Microbiota composition varies depending on what kind of sample is collected, most commonly stool samples, stool swabs or superficial rectal or intestinal biopsies, and the time of collection. Microbiota dynamics are affected by life style factors including diet and exercise that determine what nutrients reach the proximal colon and how fast these nutrients pass through (transit time). Here we review sample collection issues in gut microbiota studies and recent findings about dynamics in microbiota composition. We recommend standardizing human microbiota analysis methods to facilitate comparison and pooling between studies. Finally, we outline a need for prospective microbiota studies in large human cohorts.

Smoking and health: association between telomere length and factors impacting on human disease, quality of life and life span in a large population-based cohort under the effect of smoking duration

Reactive oxygen species (ROS) are of primary importance as they cause damage to lipids, proteins, and DNA either endogenously by cellular mechanism, or through exogenous exposure to environmental injury factors, including oxidation insult factors, such as tobacco smoke. Currently 46.3 million adults (25.7 percent of the population) are smokers. This includes 24 million men (28.1 percent of the total) and more than 22 million women (23.5 percent). The prevalence is highest among persons 25-44 years of age. Cigarette smokers have a higher risk of developing several chronic disorders. These include fatty buildups in arteries, several types of cancer and chronic obstructive pulmonary disease (lung problems). As peripheral leukocytes have been the main target of human telomere research, most of what is known about human telomere dynamics in vivo is based on these cells. Leukocyte telomere length (TL) is a complex trait that is shaped by genetic, epigenetic, and environmental determinants. In this article, we consider that smoking modifies leukocyte TL in humans and contributes to its variability among individuals, although the smoking effect on TL and its relation with other metabolic indices may accelerate biological aging and development of smoking-induced chronic diseases in a large human population-based cohorts with smoking behavior. Recent studies confirmed that individuals with shorter telomeres present a higher prevalence of arterial lesions and higher risk of cardiovascular disease mortality. This study originally suggests that efficient therapeutic protection of TL and structure in response to stresses that are known to reduce TL, such as oxidative damage or inflammation associated with tobacco smoking, would lead to better telomere maintenance. Recently, we have discovered the potential use of telomere-restorative imidazole-containing dipeptide (non-hydrolized carnosine, carcinine) based therapy for better survival of smokers. We conclude that a better therapeutic or nutritional maintenance of TL may confer healthy aging in smokers and exceptional longevity in regularly ROS-exposed human survivors.

Genetic Variation at the FTO Locus Influences RBL2 Gene Expression

OBJECTIVEGenome-wide association studies that compare the statistical association between thousands of DNA variations and a human trait have detected 958 loci across 127 different diseases and traits. However, these statistical associations only provide evidence for genomic regions likely to harbor a causal gene(s) and do not directly identify such genes. We combined gene variation and expression data in a human cohort to identify causal genes.RESEARCH DESIGN AND METHODSGlobal gene transcription activity was obtained for each individual in a large human cohort (n = 1,240). These quantitative transcript data were tested for correlation with genotype data generated from the same individuals to identify gene expression patterns influenced by the variants.RESULTSVariant rs8050136 lies within intron 1 of the FTO gene on chromosome 16 and marks a locus strongly associated with type 2 diabetes and obesity and widely replicated across many populations. We report that genetic variation at this locus does not influence FTO gene expression levels (P = 0.38), but is strongly correlated with expression of RBL2 (P = 2.7 × 10−5), ∼270,000 base pairs distant to FTO.CONCLUSIONSThese data suggest that variants at FTO influence RBL2 gene expression at large genetic distances. This observation underscores the complexity of human transcriptional regulation and highlights the utility of large human cohorts in which both genetic variation and global gene expression data are available to identify disease genes. Expedient identification of genes mediating the effects of genome-wide association study–identified loci will enable mechanism-of-action studies and accelerate understanding of human disease processes under genetic influence.

Multiple sclerosis: major histocompatibility complexity and antigen presentation

Multiple sclerosis (MS), like many putative autoimmune diseases, has been known to be associated with the human leukocyte antigen (HLA) class II region for more than 3 decades. However, exactly how HLA class II alleles increase the risk of MS is not yet conclusively known. Recent work in large human cohorts has highlighted the fact that nearly all common HLA-DRB1 allelotypes are either positively or negatively associated with the disease, detracting from allele-specific antigen presentation as the sole mechanism of MHC associated disease susceptibility. Here, we put into context recent data on the HLA class II region in MS, including allelic heterogeneity, gene-environment interactions and epigenetics. It is clear that a complete understanding of the epistatic interactions and epigenetic features of this region will be crucial to comprehending disease pathogenesis.

Abstract 5519: High Resolution Genetic Mapping Strategies for Metabolic Disease in Mice: Towards Association Based Studies

Background: Common complex diseases, such as atherosclerosis, diabetes and obesity, are the result of genetic, environmental and gene/environmental interactions. Genetic studies using mice have relied on linkage studies where two mouse strains with different disease phenotypes are crossed to identify a genetic loci conferring susceptibility or resistance to the disease. One limitation with such an approach is that linkage areas are many megabases in size and thus gene resolution is low. Recently, several whole genome association studies in large human cohorts have reported single nucleotide polymorphisms (SNPs) associated with common forms of disease. We have begun similar association based approaches to common diseases using mice. One important advantage of murine association studies is that association results can be validated biologically with knockout or transgenic approaches. Methods and Results: Our initial studies have focused on the metabolic syndrome and we have collected traits related to diabetes, adiposity and cholesterol metabolism. We have phenotyped 100 strains of mice including a panel of classic inbred mice and several panels of recombinant inbred mice (BxH, AxB, BxA and BxD). We report here our initial strategy for association in mice, power calculations and describe strain selection along with initial phenotypes and associations. Our laboratory has previously identified linkage peaks on chromosome 1 for HDL and Total Cholesterol. Studies from our laboratory and others have identified apolipoprotein A2 as a major determinate of circulating lipoproteins in mice. As a proof of principle we have focused on associations of total cholesterol and HDL cholesterol at the A2 locus on chromosome 1 and demonstrate the increased resolution of this approach. We also report loci contributing to HDL and total cholesterol levels from independent F2 crosses and coincident lipoprotein associations in the mouse diversity panel. Conclusion: Association based studies in mice have high resolution can successfully identify previously validated genes. Studies are currently ongoing to validate novel SNPs associated with other metabolic phenotypes. This research has received full or partial funding support from the American Heart Association, AHA National Center.