Early ascending growth is associated with maternal lipoprotein profile during mid and late pregnancy and in cord blood.

INTRODUCTION: Intrauterine conditions and accelerating early growth are associated with childhood obesity. It is unknown, whether fetal programming affects the early growth and could alterations in the maternal-fetal metabolome be the mediating mechanism. Therefore, we aimed to assess the associations between maternal and cord blood metabolite profile and offspring early growth. METHODS: The RADIEL study recruited 724 women at high risk for gestational diabetes mellitus (GDM) BMI ≥ 30 kg/m2 and/or prior GDM) before or in early pregnancy. Blood samples were collected once in each trimester, and from cord. Metabolomics were analyzed by targeted nuclear magnetic resonance (NMR) technique. Following up on offsprings' first 2 years growth, we discovered 3 distinct growth profiles (ascending n = 80, intermediate n = 346, and descending n = 146) by using latent class mixed models (lcmm). RESULTS: From the cohort of mother-child dyads with available growth profile data (n = 572), we have metabolomic data from 232 mothers from 1st trimester, 271 from 2nd trimester, 277 from 3rd trimester and 345 from cord blood. We have data on 220 metabolites in each trimester and 70 from cord blood. In each trimester of pregnancy, the mothers of the ascending group showed higher levels of VLDL and LDL particles, and lower levels of HDL particles (p < 0.05). When adjusted for gestational age, birth weight, sex, delivery mode, and maternal smoking, there was an association with ascending profile and 2nd trimester total cholesterol in HDL2, 3rd trimester total cholesterol in HDL2 and in HDL, VLDL size and ratio of triglycerides to phosphoglycerides (TG/PG ratio) in cord blood (p ≤ 0.002). CONCLUSION: Ascending early growth was associated with lower maternal total cholesterol in HDL in 2nd and 3rd trimester, and higher VLDL size and more adverse TG/PG ratio in cord blood. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, http://www. CLINICALTRIALS: com , NCT01698385.

Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases.

Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.

A comparative evaluation of intraoral and extraoral digital impressions: An in vivo study.

AIM: The accuracy of a dental impression is determined by two factors: "trueness" and "precision." The scanners used in dentistry are relatively new in market, and very few studies have compared the "precision" and "trueness" of intraoral scanner with the extraoral scanner. The aim of this study was to evaluate and compare accuracy of intraoral and extraoral digital impressions. MATERIALS AND METHODS: Ten dentulous participants (male/female) aged 18-45 years with an asymptomatic endodontically treated mandibular first molars with adjacent teeth present were selected for this study. The prepared test tooth was measured using a digital Vernier caliper to obtain reference datasets. The tooth was then scanned using the intraoral scanner, and the extraoral scans were obtained using the casts made from the impressions. The datasets were divided into four groups and then statistically analyzed. The test tooth preparation was done, and dimples were made using a round diamond point on the bucco-occlusal, mesio-occlusal, disto-occlusal, and linguo-occlusal lines angles, and these were used to obtain reference datasets intraorally using a digital Vernier caliper. The test tooth was then scanned with the IO scanner (CS 3500, Carestream dental) thrice and also impressions were made using addition silicone impression material (3M™ ESPE) and dental casts were poured in Type IV dental stone (Kalrock-Kalabhai Karson India Pvt. Ltd., India) which were later scanned with the EO scanner (LAVA™ Scan ST Design system [3M™ ESPE]) thrice. The Datasets obtained from Intraoral and Extraoral scanner were exported to Dental Wings software and readings were obtained. Repeated measures ANOVA test was used to compare differences between the groups and independent t-test for comparison between the readings of intraoral and extraoral scanner. Least significant difference test was used for comparison between reference datasets with intraoral and extraoral scanner, respectively. A level of statistical significance of P < 0.05 was set. RESULTS: The precision values ranged from 20.7 to 33.35 µm for intraoral scanner and 19.5 to 37 µm for extraoral scanner. The mean deviations for intraoral scanner were 19.6 µm mesiodistally (MD) and 16.4 µm buccolingually (BL) and 24.0 µm MD and 22.5 µm BL for extraoral scanner. The mean values of the intraoral scanner (413 µm) for trueness were closest to the actual measurements (459 µm) than the extraoral scanner (396 µm). CONCLUSION: The intraoral scanner showed higher "precision" and "trueness" values when compared with the extraoral scanner.

Strong influence of variants near MC4R on adiposity in children and adults: a cross-sectional study in Indian population.

Common variants near melanocortin 4 receptor (MC4R) gene are shown to be associated with adiposity but have varied effects in different age groups. Among Indians, studies have shown association of these variants with obesity in adults, but their association in children is yet to be confirmed. We evaluated association of rs17782313 and rs12970134 near MC4R with adiposity and related traits in Indians including 1362 children and 4077 adults (consisting of 2049 diabetic and 2028 nondiabetic adult subjects). Both variants rs17782313 and rs12970134 showed strong association with adiposity measures (weight, body mass index and waist circumference) in children (P-range 7.6 × 10(-5)-3.8 × 10(-12)) and nominal association in nondiabetic adults (P-range 0.05-0.003). Effect sizes on adiposity measures in children (ß range 0.22-0.26 Z-score) were ~3-fold higher compared with adults (ß range 0.06-0.08). The minor alleles of both variants showed borderline association (P-range 0.08-0.04) with risk of type 2 diabetes in adults. Meta-analysis of rs12970134 in >12 000 Indian adults corroborated its association with adiposity (P≤2.2 × 10(-9)), homeostasis model assessment-estimated insulin resistance (P=4.0 × 10(-5)) and type 2 diabetes (P=0.003) with only moderate heterogeneity, suggesting similar effect on adult Indians residing in different geographical regions. In conclusion, the study demonstrates association of variants near MC4R with obesity and related traits in Indian children and adults, with higher impact during childhood.

Effect of biological sex on human circulating lipidome: An overview of the literature.

Cardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids- low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome- and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.

Genome-wide association analysis of plasma lipidome identifies 495 genetic associations.

The human plasma lipidome captures risk for cardiometabolic diseases. To discover new lipid-associated variants and understand the link between lipid species and cardiometabolic disorders, we perform univariate and multivariate genome-wide analyses of 179 lipid species in 7174 Finnish individuals. We fine-map the associated loci, prioritize genes, and examine their disease links in 377,277 FinnGen participants. We identify 495 genome-trait associations in 56 genetic loci including 8 novel loci, with a considerable boost provided by the multivariate analysis. For 26 loci, fine-mapping identifies variants with a high causal probability, including 14 coding variants indicating likely causal genes. A phenome-wide analysis across 953 disease endpoints reveals disease associations for 40 lipid loci. For 11 coronary artery disease risk variants, we detect strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and lipid species beyond the standard lipids.

Common variants of SLAMF1 and ITLN1 on 1q21 are associated with type 2 diabetes in Indian population.

Though multiple studies link chromosomal regions 1q21-q23 and 20q13 with type 2 diabetes, fine mapping of these regions is yet to confirm gene(s) explaining the linkages. These candidate regions remain unexplored in Indians, which is a high-risk population for type 2 diabetes. Hypothesizing regulatory regions to have a more important role in complex disorders, we examined association of 207 common variants in proximal promoter and untranslated regions of genes on 1q21-23 and 20q13 with type 2 diabetes in 2115 North Indians. Further, top signals were replicated in an independent group of 2085 North Indians. Variants-rs11265455-SLAMF1 (odds ratios (OR)=1.32, P=1.1 × 10(-3)), rs1062827-F11R (OR=1.36, P=1.7 × 10(-3)) and rs12565932-F11R (OR=1.35, P=1.8 × 10(-3)) were top signals for association with type 2 diabetes whereas rs1333062-ITLN1 (OR=1.28, P=3.4 × 10(-3)) showed strongest association in body mass index-stratified analysis. Replication of these four variants confirmed associations of rs11265455-SLAMF1 (OR=1.27, P=9.1 × 10(-3)) and rs1333062-ITLN1 (OR=1.25, P=1.1 × 10(-3)) with type 2 diabetes. Meta-analysis further corroborated the association of rs11265455-SLAMF1 (OR random effect=1.29, P random effect=3.9 × 10(-5)) and rs1333062-ITLN1 (OR random effect=1.19, P random effect=1.8 × 10(-4)). In conclusion, the study demonstrates that variants of SLAMF1 and ITLN1, both implicated in inflammation, are associated with type 2 diabetes in Indians.

Quantitative online survey of self-perceived knowledge and knowledge gaps of medicines research and development among Finnish general public.

OBJECTIVES: This study explored self-reported knowledge and interest to learn more about medicines research, development and health technology assessment among Finnish general public. It also aimed to define possible knowledge gaps and needs for public education regarding these topics. DESIGN: Online survey with 503 participants. The questionnaire was originally developed as a part of the Needs Assessment Work Package of the European Patients' Academy on Therapeutic Innovation Project. The survey was carried out in Finland in 2019. METHODS: The survey was conducted as an online survey by Kantar TNS Gallup Forum online panel. The data were analysed by using the freely available programming language R. Relationships between the demographic characteristics (such as age, gender and education level) of respondents and their knowledge or interest in medicines research and development were determined using Pearson's χ2 tests. Statistically significant responses of demographic characteristics in the respondents' knowledge or interest in medicines research were determined by logistic regression. RESULTS: Of the 503 respondents (age 16-64) only 12% reported having good or very good knowledge of medicines research and development in general. Regarding health technology assessment, pharmacoeconomics and regulation, the percentage of respondents reporting good or very good knowledge was as low as 8%. Respondents were most interested in learning more about predictive and personalised medicine (47%) and least interested in medicines regulation (30%) and pharmacoeconomics (31%). CONCLUSIONS: Self-reported knowledge about medicines research and development and health technology assessment appears to be very low in Finland. Patient and public participation is recognised as an important and essential element in up-to-date medical research and assessment of new treatments. In order to participate as an active and equal partner in these processes, the public needs more information and education in these topics.

Lipidome- and Genome-Wide Study to Understand Sex Differences in Circulatory Lipids.

Background Despite well-recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex-specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex-stratified genome-wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed (P<7.0×10-4). Interestingly, 121 lipid species showed significant age-sex interactions, with opposite age-related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45- to 50-year-old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex-stratified genome-wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex- and age-specific prevention strategies.

No association of TNFRSF1B variants with type 2 diabetes in Indians of Indo-European origin.

BACKGROUND: There has been no systematic evaluation of the association between genetic variants of type 2 receptor for TNFα (TNFR2) and type 2 diabetes, despite strong biological evidence for the role of this receptor in the pathogenesis of this complex disorder. In view of this, we performed a comprehensive association analysis of TNFRSF1B variants with type 2 diabetes in 4,200 Indo-European subjects from North India. METHODS: The initial phase evaluated association of seven SNPs viz. rs652625, rs496888, rs6697733, rs945439, rs235249, rs17883432 and rs17884213 with type 2 diabetes in 2,115 participants (1,073 type 2 diabetes patients and 1,042 control subjects). Further, we conducted replication analysis of three associated SNPs in 2,085 subjects (1,047 type 2 diabetes patients and 1,038 control subjects). RESULTS: We observed nominal association of rs945439, rs235249 and rs17884213 with type 2 diabetes (P < 0.05) in the initial phase. Haplotype CC of rs945439 and rs235249 conferred increased susceptibility for type 2 diabetes [OR = 1.19 (95%CI 1.03-1.37), P = 0.019/Pperm = 0.076] whereas, TG haplotype of rs235249 and rs17884213 provided protection against type 2 diabetes [OR = 0.83 (95%CI 0.72-0.95, P = 7.2 × 10-3/Pperm = 0.019]. We also observed suggestive association of rs496888 with plasma hsCRP levels [P = 0.042]. However, the association of rs945439, rs235249 and rs17884213 with type 2 diabetes was not replicated in the second study population. Meta-analysis of the two studies also failed to detect any association with type 2 diabetes. CONCLUSIONS: Our two-stage association analysis suggests that TNFRSF1B variants are not the determinants of genetic risk of type 2 diabetes in North Indians.

Association of variants in genes involved in pancreatic ß-cell development and function with type 2 diabetes in North Indians.

Variants in genes involved in pancreatic ß-cell development and function are known to cause monogenic forms of type 2 diabetes and are also associated with complex form. In this study, we studied the genetic association of polymorphisms in such important genes with type 2 diabetes in the high-risk Indians. We genotyped 91 polymorphisms in 19 genes (ABCC8, HNF1A, HNF1B, HNF4A, INS, INSM1, ISL1, KCNJ11, MAFA, MNX1, NEUROD1, NEUROG3, NKX2.2, NKX6.1, PAX4, PAX6, PDX1, USF1 and WFS1) in 2025 unrelated North Indians of Indo-European ethnicity comprising of 1019 diabetic and 1006 non-diabetic subjects. HNF4A promoter P2 polymorphisms rs1884613 and rs2144908, which are in high linkage disequilibrium, showed significant association with type 2 diabetes (odds ratio (OR)=1.37 (95% confidence interval (CI) 1.19-1.57), P=9.4 × 10(-6) for rs1884613 and OR=1.37 (95%CI 1.20-1.57), P=6.0 × 10(-6) for rs2144908), as previously shown in other populations. We observed body mass index-dependent association of these variants with type 2 diabetes in normal-weight/lean subjects. Variants in USF1, ABCC8, ISL1 and KCNJ11 showed nominal association, while haplotypes in these genes were significantly associated. rs3812704 upstream of NEUROG3 significantly increased risk for type 2 diabetes in normal-weight/lean subjects (OR=1.68 (95%CI 1.25-2.24), P=4.9 × 10(-4)). Thus, pancreatic ß-cell development and function genes contribute to susceptibility to type 2 diabetes in North Indians.

Common variants of FTO and the risk of obesity and type 2 diabetes in Indians.

Common variants of fat mass and obesity-associated gene (FTO, fat mass- and obesity-associated gene) have been shown to be associated with obesity and type 2 diabetes in population of European and non-European ethnicity. However, studies in Indian population have provided inconsistent results. Here, we examined association of eight FTO variants (rs1421085, rs8050136, rs9939609, rs9930506, rs1861867, rs9926180, rs2540769 and rs708277) with obesity and type 2 diabetes in 5364 North Indians (2474 type 2 diabetes patients and 2890 non-diabetic controls) in two stages. None of the variants including previously reported intron 1 variants (rs1421085, rs8050136, rs9939609 and rs9930506) showed body mass index (BMI)-dependent/independent association with type 2 diabetes. However, rs1421085, rs8050136 and rs9939609 were associated with obesity status and measures of obesity (BMI, waist circumference and waist-to-hip ratio) in stage 2 and combined study population. Meta-analysis of the two study population results also revealed that rs1421085, rs8050136 and rs9939609 were significantly associated with BMI both under the random- and fixed-effect models (P (random/fixed)=0.02/0.0001, 0.004/0.0006 and 0.01/0.01, respectively). In conclusion, common variants of FTO were associated with obesity, but not with type 2 diabetes in North Indian population.

Gene prioritization in Type 2 Diabetes using domain interactions and network analysis.

BACKGROUND: Identification of disease genes for Type 2 Diabetes (T2D) by traditional methods has yielded limited success. Based on our previous observation that T2D may result from disturbed protein-protein interactions affected through disrupting modular domain interactions, here we have designed an approach to rank the candidates in the T2D linked genomic regions as plausible disease genes. RESULTS: Our approach integrates Weight value (Wv) method followed by prioritization using clustering coefficients derived from domain interaction network. Wv for each candidate is calculated based on the assumption that disease genes might be functionally related, mainly facilitated by interactions among domains of the interacting proteins. The benchmarking using a test dataset comprising of both known T2D genes and non-T2D genes revealed that Wv method had a sensitivity and specificity of 0.74 and 0.96 respectively with 9 fold enrichment. The candidate genes having a Wv > 0.5 were called High Weight Elements (HWEs). Further, we ranked HWEs by using the network property-the clustering coefficient (Ci). Each HWE with a Ci < 0.015 was prioritized as plausible disease candidates (HWEc) as previous studies indicate that disease genes tend to avoid dense clustering (with an average Ci of 0.015). This method further prioritized the identified disease genes with a sensitivity of 0.32 and a specificity of 0.98 and enriched the candidate list by 6.8 fold. Thus, from the dataset of 4052 positional candidates the method ranked 435 to be most likely disease candidates. The gene ontology sharing for the candidates showed higher representation of metabolic and signaling processes. The approach also captured genes with unknown functions which were characterized by network motif analysis. CONCLUSIONS: Prioritization of positional candidates is essential for cost-effective and an expedited discovery of disease genes. Here, we demonstrate a novel approach for disease candidate prioritization from numerous loci linked to T2D.

Evaluation of DOK5 as a susceptibility gene for type 2 diabetes and obesity in North Indian population.

BACKGROUND: Type 2 diabetes is a complex metabolic disorder with obesity being a major contributing factor in its development. Susceptibility loci for type 2 diabetes and obesity have been localized on different chromosomal regions by various genome-wide linkage scans. Of these chromosomal regions, 20q13 is one of the strongest linked regions for type 2 diabetes as well as obesity. On 20q13 lies DOK5 that seems to be a strong functional and positional candidate for type 2 diabetes and obesity because of its involvement in insulin signaling and immune responses. Hence, for the first time, we explored DOK5 as a potential type 2 diabetes and obesity susceptibility gene. METHODS: We sequenced 43 subjects for polymorphisms in functionally relevant regions of DOK5. A total of 10 SNPs that included 5 that were identified by sequencing and 5 additional SNPs from NCBI Variation Database were genotyped in 2,115 participants comprising of 1,073 patients with type 2 diabetes and 1,042 controls of Indo-European ethnicity from North India. RESULTS: We identified a novel variant in intron 7 referred to as DK176673. We found nominal association of three SNPs-rs6064099 (OR = 0.75, P = 0.019), rs873079 (OR = 0.76, P = 0.036) and DK176673 (OR = 1.55, P = 0.037) with type 2 diabetes among normal-weight subjects [BMI < 23 kg/m2]. The haplotype GGC harboring rs6068916, rs6064099 and rs873079 showed strong association with type 2 diabetes among normal-weight subjects (OR = 1.37, P/Pperm = 5.8 x 10-3/0.037). Association analysis with obesity revealed that rs6064099 is associated with reduced susceptibility for obesity (OR = 0.48, P = 6.8 x 10-3). Also, haplotype GGC conferred increased susceptibility for obesity (OR = 1.27, P/Pperm = 9.0 x 10-3/0.039). Also, rs6064099 was significantly associated with reduced BMI [median(IQR) = 24.0(20.7-27.1) vs 23.9(20.2-26.8) vs 21.8(19.2-24.7) for GG vs GC vs CC, P = 7.0 x 10-3]. CONCLUSIONS: We identified DOK5 as a novel susceptibility gene for obesity and type 2 diabetes in North Indian subjects. Association of DOK5 variants both with obesity and type 2 diabetes suggests that these variants might modulate type 2 diabetes susceptibility through obesity.

MetaPhat: Detecting and Decomposing Multivariate Associations From Univariate Genome-Wide Association Statistics.

BACKGROUND: Multivariate testing tools that integrate multiple genome-wide association studies (GWAS) have become important as the number of phenotypes gathered from study cohorts and biobanks has increased. While these tools have been shown to boost statistical power considerably over univariate tests, an important remaining challenge is to interpret which traits are driving the multivariate association and which traits are just passengers with minor contributions to the genotype-phenotypes association statistic. RESULTS: We introduce MetaPhat, a novel bioinformatics tool to conduct GWAS of multiple correlated traits using univariate GWAS results and to decompose multivariate associations into sets of central traits based on intuitive trace plots that visualize Bayesian Information Criterion (BIC) and P-value statistics of multivariate association models. We validate MetaPhat with Global Lipids Genetics Consortium GWAS results, and we apply MetaPhat to univariate GWAS results for 21 heritable and correlated polyunsaturated lipid species from 2,045 Finnish samples, detecting seven independent loci associated with a cluster of lipid species. In most cases, we are able to decompose these multivariate associations to only three to five central traits out of all 21 traits included in the analyses. We release MetaPhat as an open source tool written in Python with built-in support for multi-processing, quality control, clumping and intuitive visualizations using the R software. CONCLUSION: MetaPhat efficiently decomposes associations between multivariate phenotypes and genetic variants into smaller sets of central traits and improves the interpretation and specificity of genome-phenome associations. MetaPhat is freely available under the MIT license at: https://sourceforge.net/projects/meta-pheno-association-tracer.

Genetic variant of CCND1: association with HPV-mediated cervical cancer in Indian population.

The potential association of single nucleotide polymorphisms (SNPs) (G870A and G1722C) of CCND1 with susceptibility to cervical cancer was investigated. The study included 200 cervical cancer cases along with an equal number of healthy controls. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis and direct sequencing were employed for genotyping. We found that women carrying the 870AA genotype have a 2.49-fold increased risk for the development of cervical cancer (odds ratio (OR) 2.49; 95% confidence interval (CI) 1.51-4.09; p = 0.0004) compared with GG+GA genotypes. For the 1722 locus, the frequency of the polymorphic 'C' allele was strongly associated with a reduced risk of cervical cancer (p = 0.019; OR 0.71; 95% CI 0.54-0.94). Our data suggest that CCND1 G870A polymorphism could act as a risk factor for the development of cervical cancer. And G1722C polymorphism may play a protective role against the development of human papillomavirus-associated cervical cancer among Indian women.

Coronary Artery Disease Risk and Lipidomic Profiles Are Similar in Hyperlipidemias With Family History and Population-Ascertained Hyperlipidemias.

Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low-density lipoprotein cholesterol ( LDL -C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population-based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first-degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL -C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta-analysis of the hyperlipidemic families and the population cohort (high LDL -C: hazard ratio, 1.74 [95% CI, 1.48-2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09-1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid-lowering medication. In lipidomic profiling, high LDL -C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P-value range 0.038-2.3×10-56). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL -C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population-based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL -C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

Genetic architecture of human plasma lipidome and its link to cardiovascular disease.

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10-8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.

Sequence and structural properties of identical mutations with varying phenotypes in human coagulation factor IX.

Mutations in human coagulation factor IX cause an X-linked bleeding disorder Hemophilia B, which can be classified as severe, moderately severe and mild based on the plasma levels of factor IX among affected individuals with respect to normal factor IX activity assayed in the patients' plasma (<1%, 2-5%, 6-30%, respectively). Recently, we identified hemophilia B to be a disease with mutations showing clinical variation and speculated that this phenotypic heterogeneity might be a replacement-specific property. Here, we have analyzed the differences in sequence and structural properties among identical mutations with varying phenotypes (IMVPs) by comparing with mutations with uniform phenotypes (MUPs), with recurring reports in Haemophilia B mutation database. Classification of mutations into IMVPs and MUPs has been done based on rigorous systematic evaluation of the clotting activity each mutation is associated with. IMVPs (n = 51) occur in less conserved mutant sites with more tolerated substitutions compared to MUPs (n = 100). A preponderance of CpG site mutations and Arg as the mutated residue in IMVPs compared to Cys in MUPs was observed. Hence, a CpG site substitution at less conserved Arg site might have an increased propensity of expressing variable phenotypes. The changes in intrinsic properties associated with the mutation are less drastic for IMVPs than for MUPs, though no significant differences were observed in structural properties. Based on this study and available literature we speculate that modifier genes at other loci, epigenetic interactions and environment may serve individually or cumulatively to bring about the clinical variation implicating hemophilia B to be deviation from classical Mendelian disorder with complete penetrance. We demonstrate that phenotypic heterogeneity appears to be site-specific also owing to the lesser conservation of the mutant site.

Omic personality: implications of stable transcript and methylation profiles for personalized medicine.

BACKGROUND: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes. METHODS: Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. RESULTS: Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression. CONCLUSIONS: People express an "omic personality" consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.