Epithelial-Myoepithelial Carcinoma of the Breast with Rhabdoid Features.

Epithelial-myoepithelial carcinoma of the breast is a rare biphasic tumor composed of intermixed malignant epithelial and myoepithelial components. Myoepithelial cells are known to adopt varied morphologies, including spindle, chondroid, clear cell, and rhabdoid morphologies, and can represent a diagnostic challenge when isolated on biopsy. Rhabdomyosarcoma, phyllodes tumor, metaplastic carcinoma, and myoepithelial carcinoma are primary breast tumors that all have been shown to exhibit rhabdoid features, whether representing true differentiation or morphological mimic. We here report an epithelial-myoepithelial carcinoma of the breast with rhabdoid features in a 76-year-old woman. The rhabdoid-appearing myoepithelial cells are negative for myogenin, consistent with a rhabdoid-like morphology rather than a true rhabdoid differentiation, comparably to previously described myoepithelial carcinoma with rhabdoid features. To our knowledge, this is the first reported case of epithelial-myoepithelial carcinoma of the breast with rhabdoid features and thus adds another entity to the differential diagnosis of breast lesions with rhabdoid features.

Genetic determinants of adiponectin regulation revealed by pregnancy.

OBJECTIVE: This study investigated genetic determinants of adiponectin during pregnancy to reveal novel biology of adipocyte regulation. METHODS: A genome-wide association study was conducted in 1,322 pregnant women from the Hyperglycemia and Adverse Pregnancy Outcome Study with adiponectin measured at ∼28 weeks of gestation. Variants reaching P < 5×10-5 for de novo genotyping in two replication cohorts (Genetics of Glycemic regulation in Gestation and Growth N = 522; ECOGENE-21 N = 174) were selected. RESULTS: In the combined meta-analysis, the maternal T allele of rs900400 located on chr3q25 (near LEKR1/CCNL1) was associated with lower maternal adiponectin (ß ± standard error [SE] = -0.18 ± 0.03 standard deviation [SD] of adiponectin per risk allele; P = 1.5 ×10-8 ; N = 2,004; multivariable adjusted models). In contrast, rs900400 showed only nominal association with adiponectin in a large sample of nonpregnant women (ß ± SE = -0.012 ± 0.006; P = 0.05; N = 16,678 women from the ADIPOgen consortium). The offspring rs900400 T risk allele was associated with greater neonatal skinfold thickness (ß ±SE = 0.19 ± 0.04 SD per risk allele; P = 4.1×10-8 ; N = 1,489) and higher cord blood leptin (ß ± SE = 0.28 ± 0.05 log-leptin per risk allele; P = 8.2 ×10-9 ; N = 502), but not with cord blood adiponectin (P = 0.23; N = 495). The T allele of rs900400 was associated with higher expression of TIPARP in adipocytes. CONCLUSIONS: These investigations of adipokines during pregnancy and early life suggest that rs900400 has a role in adipocyte function.

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk.

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.

The causal effect of vitamin D binding protein (DBP) levels on calcemic and cardiometabolic diseases: a Mendelian randomization study.

BACKGROUND: Observational studies have shown that vitamin D binding protein (DBP) levels, a key determinant of 25-hydroxy-vitamin D (25OHD) levels, and 25OHD levels themselves both associate with risk of disease. If 25OHD levels have a causal influence on disease, and DBP lies in this causal pathway, then DBP levels should likewise be causally associated with disease. We undertook a Mendelian randomization study to determine whether DBP levels have causal effects on common calcemic and cardiometabolic disease. METHODS AND FINDINGS: We measured DBP and 25OHD levels in 2,254 individuals, followed for up to 10 y, in the Canadian Multicentre Osteoporosis Study (CaMos). Using the single nucleotide polymorphism rs2282679 as an instrumental variable, we applied Mendelian randomization methods to determine the causal effect of DBP on calcemic (osteoporosis and hyperparathyroidism) and cardiometabolic diseases (hypertension, type 2 diabetes, coronary artery disease, and stroke) and related traits, first in CaMos and then in large-scale genome-wide association study consortia. The effect allele was associated with an age- and sex-adjusted decrease in DBP level of 27.4 mg/l (95% CI 24.7, 30.0; n = 2,254). DBP had a strong observational and causal association with 25OHD levels (p = 3.2 × 10(-19)). While DBP levels were observationally associated with calcium and body mass index (BMI), these associations were not supported by causal analyses. Despite well-powered sample sizes from consortia, there were no associations of rs2282679 with any other traits and diseases: fasting glucose (0.00 mmol/l [95% CI -0.01, 0.01]; p = 1.00; n = 46,186); fasting insulin (0.01 pmol/l [95% CI -0.00, 0.01,]; p = 0.22; n = 46,186); BMI (0.00 kg/m(2) [95% CI -0.01, 0.01]; p = 0.80; n = 127,587); bone mineral density (0.01 g/cm(2) [95% CI -0.01, 0.03]; p = 0.36; n = 32,961); mean arterial pressure (-0.06 mm Hg [95% CI -0.19, 0.07]); p = 0.36; n = 28,775); ischemic stroke (odds ratio [OR]  = 1.00 [95% CI 0.97, 1.04]; p = 0.92; n = 12,389/62,004 cases/controls); coronary artery disease (OR = 1.02 [95% CI 0.99, 1.05]; p = 0.31; n = 22,233/64,762); or type 2 diabetes (OR = 1.01 [95% CI 0.97, 1.05]; p = 0.76; n = 9,580/53,810). CONCLUSIONS: DBP has no demonstrable causal effect on any of the diseases or traits investigated here, except 25OHD levels. It remains to be determined whether 25OHD has a causal effect on these outcomes independent of DBP. Please see later in the article for the Editors' Summary.

Genetic evidence for a normal-weight "metabolically obese" phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes.

The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy-a reduction in subcutaneous adipose tissue-it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, CAD, and T2D. We aimed to test the hypothesis that common alleles associated with IR also influence the wider clinical and biochemical profile of monogenic IR. We selected 19 common genetic variants associated with fasting insulin-based measures of IR. We used hierarchical clustering and results from genome-wide association studies of eight nondisease outcomes of monogenic IR to group these variants. We analyzed genetic risk scores against disease outcomes, including 12,171 T2D cases, 40,365 CAD cases, and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (ß = 0.018; P = 4 × 10(-29)), lower HDL cholesterol (ß = -0.020; P = 7 × 10(-37)), greater hepatic steatosis (ß = 0.021; P = 3 × 10(-4)), higher alanine transaminase (ß = 0.002; P = 3 × 10(-5)), lower sex-hormone-binding globulin (ß = -0.010; P = 9 × 10(-13)), and lower adiponectin (ß = -0.015; P = 2 × 10(-26)). The same risk alleles were associated with lower BMI (per-allele ß = -0.008; P = 7 × 10(-8)) and increased visceral-to-subcutaneous adipose tissue ratio (ß = -0.015; P = 6 × 10(-7)). Individuals carrying ≥17 fasting insulin-raising alleles (5.5% population) were slimmer (0.30 kg/m(2)) but at increased risk of T2D (odds ratio [OR] 1.46; per-allele P = 5 × 10(-13)), CAD (OR 1.12; per-allele P = 1 × 10(-5)), and increased blood pressure (systolic and diastolic blood pressure of 1.21 mmHg [per-allele P = 2 × 10(-5)] and 0.67 mmHg [per-allele P = 2 × 10(-4)], respectively) compared with individuals carrying ≤9 risk alleles (5.5% population). Our results provide genetic evidence for a link between the three diseases of the "metabolic syndrome" and point to reduced subcutaneous adiposity as a central mechanism.

Pleiotropic genes for metabolic syndrome and inflammation.

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.

In healthy adults, biological activity of vitamin D, as assessed by serum PTH, is largely independent of DBP concentrations.

Vitamin D insufficiency, as measured by 25-hydroxyvitamin D (25[OH]D) levels, has been associated with important health outcomes. The majority of vitamin D in circulation is bound to vitamin D-binding protein (DBP) and albumin, and recent genetic studies have demonstrated that serum DBP is a major determinant of 25(OH)D concentrations in adults. The impact of circulating DBP levels on vitamin D's biologic action, is unclear, but is of particular relevance to vitamin D epidemiology, because a lack of control for DBP levels could strongly influence the association of vitamin D with disease. Serum parathyroid hormone (PTH) levels can act as a biological readout of 25(OH)D activity. We therefore assessed the relationship between serum total and free 25(OH)D and PTH with and without adjusting for DBP, in 2073 subjects of European descent. Total 25(OH)D levels correlated positively (r = 0.19, p = 1.8 × 10(-17)) with DBP, whereas the free 25(OH)D correlated negatively (r = -0.14, p = 5.0 × 10(-12)). Total and free 25(OH)D levels correlated negatively with PTH (r = -0.29, p = 1.3 × 10(-39); r = -0.26, p = 1.9 × 10(-33), respectively). Including age, body mass index (BMI), sex, estimated glomerular filtration rate, calcium, and season of blood draw as covariates, total 25(OH)D levels were significantly associated with log-transformed PTH (lnPTH) levels (linear term: ß = -0.010, p < 0.0001, squared term: ß = 0.00004, p < 0.0001) and this association was not changed by adjusting for DBP. These findings provide evidence that in a largely vitamin D-sufficient cohort, the biological effect of vitamin D on PTH levels is mainly independent of DBP concentration. Accordingly, this study may provide useful information for studies investigating the relationship between vitamin D, DBP, and disease.

Mendelian randomization studies do not support a causal role for reduced circulating adiponectin levels in insulin resistance and type 2 diabetes.

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

The shared allelic architecture of adiponectin levels and coronary artery disease.

OBJECTIVE: A large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. METHODS: Using 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium (n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium (n = 85,274). RESULTS: In single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing (P < 4.4 × 10(-4)). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD (P = 5.4 × 10(-7)). CONCLUSION: These findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

An assessment of the shared allelic architecture between type II diabetes and prostate cancer.

BACKGROUND: To determine whether the alleles that influence type II diabetes risk and glycemic traits also influence prostate cancer risk. METHODS: We used a multiple single-nucleotide polymorphisms (SNP) genotypic risk score to assess the average effect of alleles that increase type II diabetes risk or worsen glycemic traits on risk of prostate cancer in 19,662 prostate cancer cases and 19,715 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium and 5,504 prostate cancer cases and 5,834 controls from the Cancer Research UK (CRUK) prostate cancer study. RESULTS: Calculating the average additive effect of type II diabetes or glycemic trait risk alleles on prostate cancer risk using a logistic model revealed no evidence of a shared allelic architecture between type II diabetes, or worsened glycemic status, with prostate cancer risk [OR for type II diabetes alleles: 1.00 (P = 0.58), fasting glycemia alleles: 1.00 (P = 0.67), HbA1c alleles: 1.00 (P = 0.93), 2-hour OGTT alleles: 1.01 (P = 0.14), and HOMA-B alleles: 0.99 (P = 0.57)]. CONCLUSIONS: Using genetic data from large consortia, we found no evidence for a shared genetic etiology of type II diabetes or glycemic risk with prostate cancer. IMPACT: Our results showed that alleles influencing type II diabetes and related glycemic traits were not found to be associated with the risk of prostate cancer.

Adjusted sequence kernel association test for rare variants controlling for cryptic and family relatedness.

Recent progress in sequencing technologies makes it possible to identify rare and unique variants that may be associated with complex traits. However, the results of such efforts depend crucially on the use of efficient statistical methods and study designs. Although family-based designs might enrich a data set for familial rare disease variants, most existing rare variant association approaches assume independence of all individuals. We introduce here a framework for association testing of rare variants in family-based designs. This framework is an adaptation of the sequence kernel association test (SKAT) which allows us to control for family structure. Our adjusted SKAT (ASKAT) combines the SKAT approach and the factored spectrally transformed linear mixed models (FaST-LMMs) algorithm to capture family effects based on a LMM incorporating the realized proportion of the genome that is identical by descent between pairs of individuals, and using restricted maximum likelihood methods for estimation. In simulation studies, we evaluated type I error and power of this proposed method and we showed that regardless of the level of the trait heritability, our approach has good control of type I error and good power. Since our approach uses FaST-LMM to calculate variance components for the proposed mixed model, ASKAT is reasonably fast and can analyze hundreds of thousands of markers. Data from the UK twins consortium are presented to illustrate the ASKAT methodology.

Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts.

BACKGROUND: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. METHODS AND FINDINGS: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²7). The BMI allele score was associated both with BMI (p = 6.30×10⁻6²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). CONCLUSIONS: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Genetic regulation of vitamin D levels.

Vitamin D plays several roles in the body, influencing bone health as well as serum calcium and phosphate levels. Further, vitamin D may modify immune function, cell proliferation, differentiation, and apoptosis. Vitamin D deficiency has been associated with numerous health outcomes, including bone disease, cancer, autoimmune disease, infectious disease, type 1 and type 2 diabetes, hypertension, and heart disease, although it is unclear whether or not these associations are causal. Various twin and family studies have demonstrated moderate to high heritability for circulating vitamin D levels. Accordingly, many studies have investigated the genetic determinants of this hormone. Recent advances in the methodology of large-scale genetic association studies, including coordinated international collaboration, have identified associations of CG, DHCR1, CYP2R1, VDR, and CYP24A1 with serum levels of vitamin D. Here, we review the genetic determinants of vitamin D levels by focusing on new findings arising from candidate gene and genomewide association studies.

Copy number variation of the APC gene is associated with regulation of bone mineral density.

INTRODUCTION: Genetic studies of osteoporosis have commonly examined SNPs in candidate genes or whole genome analyses, but insertions and deletions of DNA, collectively called copy number variations (CNVs), also comprise a large amount of the genetic variability between individuals. Previously, SNPs in the APC gene have been strongly associated with femoral neck and lumbar spine volumetric bone mineral density in older men. In addition, familial adenomatous polyposis patients carrying heterozygous mutations in the APC gene have been shown to have significantly higher mean bone mineral density than age- and sex-matched controls suggesting the importance of this gene in regulating bone mineral density. We examined CNV within the APC gene region to test for association with bone mineral density. METHODS: DNA was extracted from venous blood, genotyped using the Human Hap610 arrays and CNV determined from the fluorescence intensity data in 2070 Caucasian men and women aged 47.0 ± 13.0 (mean ± SD) years, to assess the effects of the CNV on bone mineral density at the forearm, spine and total hip sites. RESULTS: Data for covariate adjusted bone mineral density from subjects grouped by APC CNV genotype showed significant difference (P=0.02-0.002). Subjects with a single copy loss of APC had a 7.95%, 13.10% and 13.36% increase in bone mineral density at the forearm, spine and total hip sites respectively, compared to subjects with two copies of the APC gene. CONCLUSIONS: These data support previous findings of APC regulating bone mineral density and demonstrate that a novel CNV of the APC gene is significantly associated with bone mineral density in Caucasian men and women.

Multiple regression methods show great potential for rare variant association tests.

The investigation of associations between rare genetic variants and diseases or phenotypes has two goals. Firstly, the identification of which genes or genomic regions are associated, and secondly, discrimination of associated variants from background noise within each region. Over the last few years, many new methods have been developed which associate genomic regions with phenotypes. However, classical methods for high-dimensional data have received little attention. Here we investigate whether several classical statistical methods for high-dimensional data: ridge regression (RR), principal components regression (PCR), partial least squares regression (PLS), a sparse version of PLS (SPLS), and the LASSO are able to detect associations with rare genetic variants. These approaches have been extensively used in statistics to identify the true associations in data sets containing many predictor variables. Using genetic variants identified in three genes that were Sanger sequenced in 1998 individuals, we simulated continuous phenotypes under several different models, and we show that these feature selection and feature extraction methods can substantially outperform several popular methods for rare variant analysis. Furthermore, these approaches can identify which variants are contributing most to the model fit, and therefore both goals of rare variant analysis can be achieved simultaneously with the use of regression regularization methods. These methods are briefly illustrated with an analysis of adiponectin levels and variants in the ADIPOQ gene.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

The empirical power of rare variant association methods: results from sanger sequencing in 1,998 individuals.

The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the contribution of rare variation to complex disease etiology. Nevertheless, no empirical estimates comparing their relative power are available. We therefore assessed the parameters that influence their statistical power in 1,998 individuals Sanger-sequenced at seven genes by modeling different distributions of effect, proportions of causal variants, and direction of the associations (deleterious, protective, or both) in simulated continuous trait and case/control phenotypes. Our results demonstrate that the power of recently proposed statistical methods depend strongly on the underlying hypotheses concerning the relationship of phenotypes with each of these three factors. No method demonstrates consistently acceptable power despite this large sample size, and the performance of each method depends upon the underlying assumption of the relationship between rare variants and complex traits. Sensitivity analyses are therefore recommended to compare the stability of the results arising from different methods, and promising results should be replicated using the same method in an independent sample. These findings provide guidance in the analysis and interpretation of the role of rare base-pair variation in the etiology of complex traits and diseases.

Genetic polymorphisms of innate immunity-related inflammatory pathways and their association with factors related to type 2 diabetes.

BACKGROUND: Type 2 diabetes mellitus (T2DM) has been linked to a state of pre-clinical chronic inflammation resulting from abnormalities in the innate immune pathway. Serum levels of pro-inflammatory cytokines and acute-phase proteins, collectively known as 'inflammatory network', are elevated in the pre-, or early, stages of T2DM and increase with disease progression. Genetic variation can affect the innate immune response to certain environmental factors, and may, therefore, determine an individual's lifetime risk of disease. METHODS: We conducted a cross-sectional study in 6,720 subjects from the Twins UK Registry to evaluate the association between 18 single nucleotide polymorphisms (SNPs) in five genes (TLR4, IL1A, IL6, TNFA, and CRP) along the innate immunity-related inflammatory pathway and biomarkers of predisposition to T2DM [fasting insulin and glucose, HDL- and LDL- cholesterols, triglycerides (TGs), amyloid-A, sensitive C-reactive protein (sCRP) and vitamin D binding protein (VDBP) and body mass index (BMI)]. RESULTS: Of 18 the SNPs examined for their association with nine metabolic phenotypes of interest, six were significantly associated with five metabolic phenotypes (Bonferroni correction, P ≤ 0.0027). Fasting insulin was associated with SNPs in IL6 and TNFA, serum HDL-C with variants of TNFA and CRP and serum sCRP level with SNPs in CRP. Cross-correlation analysis among the different metabolic factors related to risk of T2DM showed several significant associations. For example, BMI was directly correlated with glucose (r = 0.11), insulin (r = 0.15), sCRP (r = 0.23), LDL-C (r = 0.067) and TGs (r = 0.18) but inversely with HDL-C (r = -0.14). sCRP was also positively correlated (P < 0.0001) with insulin (r = 0.17), amyloid-A (r = 0.39), TGs (r = 0.26), and VDBP (r = 0.36) but inversely with HDL-C (r = -0.12). CONCLUSION: Genetic variants in the innate immunity pathway and its related inflammatory cascade is associated with some metabolic risk factors for T2DM; an observation that may provide a rationale for further studying their role as biomarkers for disease early risk prediction.

An efficient paradigm for genetic epidemiology cohort creation.

Development of novel methodologies to efficiently create large genetic epidemiology cohorts is needed. Here we describe a rapid, precise and cost-efficient method for collection of DNA from cases previously experiencing an osteoporotic fracture by identifying cases using and administrative health-care databases. Over the course of 14 months we collected DNA from 1,130 women experiencing an osteoporotic fracture, at a cost of $54 per sample. This cohort is among the larger DNA osteoporotic fracture collections in the world. The novel method described addresses a major unmet health care research need and is widely applicable to any disease that can be identified accurately through administrative data.