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1.  Genome-Wide Association of Body Fat Distribution in African Ancestry Populations Suggests New Loci 
Liu, Ching-Ti | Monda, Keri L. | Taylor, Kira C. | Lange, Leslie | Demerath, Ellen W. | Palmas, Walter | Wojczynski, Mary K. | Ellis, Jaclyn C. | Vitolins, Mara Z. | Liu, Simin | Papanicolaou, George J. | Irvin, Marguerite R. | Xue, Luting | Griffin, Paula J. | Nalls, Michael A. | Adeyemo, Adebowale | Liu, Jiankang | Li, Guo | Ruiz-Narvaez, Edward A. | Chen, Wei-Min | Chen, Fang | Henderson, Brian E. | Millikan, Robert C. | Ambrosone, Christine B. | Strom, Sara S. | Guo, Xiuqing | Andrews, Jeanette S. | Sun, Yan V. | Mosley, Thomas H. | Yanek, Lisa R. | Shriner, Daniel | Haritunians, Talin | Rotter, Jerome I. | Speliotes, Elizabeth K. | Smith, Megan | Rosenberg, Lynn | Mychaleckyj, Josyf | Nayak, Uma | Spruill, Ida | Garvey, W. Timothy | Pettaway, Curtis | Nyante, Sarah | Bandera, Elisa V. | Britton, Angela F. | Zonderman, Alan B. | Rasmussen-Torvik, Laura J. | Chen, Yii-Der Ida | Ding, Jingzhong | Lohman, Kurt | Kritchevsky, Stephen B. | Zhao, Wei | Peyser, Patricia A. | Kardia, Sharon L. R. | Kabagambe, Edmond | Broeckel, Ulrich | Chen, Guanjie | Zhou, Jie | Wassertheil-Smoller, Sylvia | Neuhouser, Marian L. | Rampersaud, Evadnie | Psaty, Bruce | Kooperberg, Charles | Manson, JoAnn E. | Kuller, Lewis H. | Ochs-Balcom, Heather M. | Johnson, Karen C. | Sucheston, Lara | Ordovas, Jose M. | Palmer, Julie R. | Haiman, Christopher A. | McKnight, Barbara | Howard, Barbara V. | Becker, Diane M. | Bielak, Lawrence F. | Liu, Yongmei | Allison, Matthew A. | Grant, Struan F. A. | Burke, Gregory L. | Patel, Sanjay R. | Schreiner, Pamela J. | Borecki, Ingrid B. | Evans, Michele K. | Taylor, Herman | Sale, Michele M. | Howard, Virginia | Carlson, Christopher S. | Rotimi, Charles N. | Cushman, Mary | Harris, Tamara B. | Reiner, Alexander P. | Cupples, L. Adrienne | North, Kari E. | Fox, Caroline S.
PLoS Genetics  2013;9(8):e1003681.
Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0×10−6 were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10−8 for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10−8 for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5×10−8; RREB1: p = 5.7×10−8). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.
Author Summary
Central obesity is a marker of body fat distribution and is known to have a genetic underpinning. Few studies have reported genome-wide association study (GWAS) results among individuals of predominantly African ancestry (AA). We performed a collaborative meta-analysis in order to identify genetic loci associated with body fat distribution in AA individuals using waist circumference (WC) and waist to hip ratio (WHR) as measures of fat distribution, with and without adjustment for body mass index (BMI). We uncovered 2 genetic loci potentially associated with fat distribution: LHX2 in association with WC-adjusted-for-BMI and at RREB1 for WHR-adjusted-for-BMI. Six of fourteen previously reported loci for waist in EA populations were significant in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). These findings reinforce the concept that there are loci for body fat distribution that are independent of generalized adiposity.
PMCID: PMC3744443  PMID: 23966867
2.  Genetic Predisposition to Increased Blood Cholesterol and Triglyceride Lipid Levels and Risk of Alzheimer Disease: A Mendelian Randomization Analysis 
PLoS Medicine  2014;11(9):e1001713.
In this study, Proitsi and colleagues use a Mendelian randomization approach to dissect the causal nature of the association between circulating lipid levels and late onset Alzheimer's Disease (LOAD) and find that genetic predisposition to increased plasma cholesterol and triglyceride lipid levels is not associated with elevated LOAD risk.
Please see later in the article for the Editors' Summary
Although altered lipid metabolism has been extensively implicated in the pathogenesis of Alzheimer disease (AD) through cell biological, epidemiological, and genetic studies, the molecular mechanisms linking cholesterol and AD pathology are still not well understood and contradictory results have been reported. We have used a Mendelian randomization approach to dissect the causal nature of the association between circulating lipid levels and late onset AD (LOAD) and test the hypothesis that genetically raised lipid levels increase the risk of LOAD.
Methods and Findings
We included 3,914 patients with LOAD, 1,675 older individuals without LOAD, and 4,989 individuals from the general population from six genome wide studies drawn from a white population (total n = 10,578). We constructed weighted genotype risk scores (GRSs) for four blood lipid phenotypes (high-density lipoprotein cholesterol [HDL-c], low-density lipoprotein cholesterol [LDL-c], triglycerides, and total cholesterol) using well-established SNPs in 157 loci for blood lipids reported by Willer and colleagues (2013). Both full GRSs using all SNPs associated with each trait at p<5×10−8 and trait specific scores using SNPs associated exclusively with each trait at p<5×10−8 were developed. We used logistic regression to investigate whether the GRSs were associated with LOAD in each study and results were combined together by meta-analysis. We found no association between any of the full GRSs and LOAD (meta-analysis results: odds ratio [OR] = 1.005, 95% CI 0.82–1.24, p = 0.962 per 1 unit increase in HDL-c; OR = 0.901, 95% CI 0.65–1.25, p = 0.530 per 1 unit increase in LDL-c; OR = 1.104, 95% CI 0.89–1.37, p = 0.362 per 1 unit increase in triglycerides; and OR = 0.954, 95% CI 0.76–1.21, p = 0.688 per 1 unit increase in total cholesterol). Results for the trait specific scores were similar; however, the trait specific scores explained much smaller phenotypic variance.
Genetic predisposition to increased blood cholesterol and triglyceride lipid levels is not associated with elevated LOAD risk. The observed epidemiological associations between abnormal lipid levels and LOAD risk could therefore be attributed to the result of biological pleiotropy or could be secondary to LOAD. Limitations of this study include the small proportion of lipid variance explained by the GRS, biases in case-control ascertainment, and the limitations implicit to Mendelian randomization studies. Future studies should focus on larger LOAD datasets with longitudinal sampled peripheral lipid measures and other markers of lipid metabolism, which have been shown to be altered in LOAD.
Please see later in the article for the Editors' Summary
Editors' Summary
Currently, about 44 million people worldwide have dementia, a group of brain disorders characterized by an irreversible decline in memory, communication, and other “cognitive” functions. Dementia mainly affects older people and, because people are living longer, experts estimate that more than 135 million people will have dementia by 2050. The commonest form of dementia is Alzheimer disease. In this type of dementia, protein clumps called plaques and neurofibrillary tangles form in the brain and cause its degeneration. The earliest sign of Alzheimer disease is usually increasing forgetfulness. As the disease progresses, affected individuals gradually lose their ability to deal with normal daily activities such as dressing. They may become anxious or aggressive or begin to wander. They may also eventually lose control of their bladder and of other physical functions. At present, there is no cure for Alzheimer disease although some of its symptoms can be managed with drugs. Most people with the disease are initially cared for at home by relatives and other unpaid carers, but many patients end their days in a care home or specialist nursing home.
Why Was This Study Done?
Several lines of evidence suggest that lipid metabolism (how the body handles cholesterol and other fats) is altered in patients whose Alzheimer disease develops after the age of 60 years (late onset Alzheimer disease, LOAD). In particular, epidemiological studies (observational investigations that examine the patterns and causes of disease in populations) have found an association between high amounts of cholesterol in the blood in midlife and the risk of LOAD. However, observational studies cannot prove that abnormal lipid metabolism (dyslipidemia) causes LOAD. People with dyslipidemia may share other characteristics that cause both dyslipidemia and LOAD (confounding) or LOAD might actually cause dyslipidemia (reverse causation). Here, the researchers use “Mendelian randomization” to examine whether lifetime changes in lipid metabolism caused by genes have a causal impact on LOAD risk. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the effect of a modifiable risk factor and the outcome of interest. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. So, if dyslipidemia causes LOAD, genetic variants that affect lipid metabolism should be associated with an altered risk of LOAD.
What Did the Researchers Do and Find?
The researchers investigated whether genetic predisposition to raised lipid levels increased the risk of LOAD in 10,578 participants (3,914 patients with LOAD, 1,675 elderly people without LOAD, and 4,989 population controls) using data collected in six genome wide studies looking for gene variants associated with Alzheimer disease. The researchers constructed a genotype risk score (GRS) for each participant using genetic risk markers for four types of blood lipids on the basis of the presence of single nucleotide polymorphisms (SNPs, a type of gene variant) in their DNA. When the researchers used statistical methods to investigate the association between the GRS and LOAD among all the study participants, they found no association between the GRS and LOAD.
What Do These Findings Mean?
These findings suggest that the genetic predisposition to raised blood levels of four types of lipid is not causally associated with LOAD risk. The accuracy of this finding may be affected by several limitations of this study, including the small proportion of lipid variance explained by the GRS and the validity of several assumptions that underlie all Mendelian randomization studies. Moreover, because all the participants in this study were white, these findings may not apply to people of other ethnic backgrounds. Given their findings, the researchers suggest that the observed epidemiological associations between abnormal lipid levels in the blood and variation in lipid levels for reasons other than genetics, or to LOAD risk could be secondary to variation in lipid levels for reasons other than genetics, or to LOAD, a possibility that can be investigated by studying blood lipid levels and other markers of lipid metabolism over time in large groups of patients with LOAD. Importantly, however, these findings provide new information about the role of lipids in LOAD development that may eventually lead to new therapeutic and public-health interventions for Alzheimer disease.
Additional Information
Please access these websites via the online version of this summary at
The UK National Health Service Choices website provides information (including personal stories) about Alzheimer's disease
The UK not-for-profit organization Alzheimer's Society provides information for patients and carers about dementia, including personal experiences of living with Alzheimer's disease
The US not-for-profit organization Alzheimer's Association also provides information for patients and carers about dementia and personal stories about dementia
Alzheimer's Disease International is the international federation of Alzheimer disease associations around the world; it provides links to individual associations, information about dementia, and links to World Alzheimer Reports
MedlinePlus provides links to additional resources about Alzheimer's disease (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
PMCID: PMC4165594  PMID: 25226301
3.  Impact of nine common type 2 diabetes risk polymorphisms in Asian Indian Sikhs: PPARG2 (Pro12Ala), IGF2BP2, TCF7L2 and FTO variants confer a significant risk 
BMC Medical Genetics  2008;9:59.
Recent genome-wide association (GWA) studies have identified several unsuspected genes associated with type 2 diabetes (T2D) with previously unknown functions. In this investigation, we have examined the role of 9 most significant SNPs reported in GWA studies: [peroxisome proliferator-activated receptor gamma 2 (PPARG2; rs 1801282); insulin-like growth factor two binding protein 2 (IGF2BP2; rs 4402960); cyclin-dependent kinase 5, a regulatory subunit-associated protein1-like 1 (CDK5; rs7754840); a zinc transporter and member of solute carrier family 30 (SLC30A8; rs13266634); a variant found near cyclin-dependent kinase inhibitor 2A (CDKN2A; rs10811661); hematopoietically expressed homeobox (HHEX; rs 1111875); transcription factor-7-like 2 (TCF7L2; rs 10885409); potassium inwardly rectifying channel subfamily J member 11(KCNJ11; rs 5219); and fat mass obesity-associated gene (FTO; rs 9939609)].
We genotyped these SNPs in a case-control sample of 918 individuals consisting of 532 T2D cases and 386 normal glucose tolerant (NGT) subjects of an Asian Sikh community from North India. We tested the association between T2D and each SNP using unconditional logistic regression before and after adjusting for age, gender, and other covariates. We also examined the impact of these variants on body mass index (BMI), waist to hip ratio (WHR), fasting insulin, and glucose and lipid levels using multiple linear regression analysis.
Four of the nine SNPs revealed a significant association with T2D; PPARG2 (Pro12Ala) [odds ratio (OR) 0.12; 95% confidence interval (CI) (0.03–0.52); p = 0.005], IGF2BP2 [OR 1.37; 95% CI (1.04–1.82); p = 0.027], TCF7L2 [OR 1.64; 95% CI (1.20–2.24); p = 0.001] and FTO [OR 1.46; 95% CI (1.11–1.93); p = 0.007] after adjusting for age, sex and BMI. Multiple linear regression analysis revealed significant association of two of nine investigated loci with diabetes-related quantitative traits. The 'C' (risk) allele of CDK5 (rs 7754840) was significantly associated with decreased HDL-cholesterol levels in both NGT (p = 0.005) and combined (NGT and T2D) (0.005) groups. The less common 'C' (risk) allele of TCF7L2 (rs 10885409) was associated with increased LDL-cholesterol (p = 0.010) in NGT and total and LDL-cholesterol levels (p = 0.008; p = 0.003, respectively) in combined cohort.
To our knowledge, this is first study reporting the role of some recently emerged loci with T2D in a high risk population of Asian Indian origin. Further investigations are warranted to understand the pathway-based functional implications of these important loci in T2D pathophysiology in different ethnicities.
PMCID: PMC2481250  PMID: 18598350
4.  Knowledge-Driven Analysis Identifies a Gene–Gene Interaction Affecting High-Density Lipoprotein Cholesterol Levels in Multi-Ethnic Populations 
PLoS Genetics  2012;8(5):e1002714.
Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected Pc = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (Pc = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; Pc = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (Pc = 0.004) and in the Hispanic American sample from MESA (Pc = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations.
Author Summary
Genome-wide association studies (GWAS) have identified many loci associated with complex human traits or diseases. However, the fraction of heritable variation explained by these loci is often relatively low. Gene–gene interactions might play a significant role in complex traits or diseases and are one of the many possible factors contributing to the missing heritability. However, to date only a few interactions have been found and validated in GWAS due to the limited power caused by the need for multiple-testing correction for the very large number of tests conducted. Here, we used three types of prior knowledge, known GWAS hits, protein–protein interactions, and pathway information, to guide our search for gene–gene interactions affecting four lipid levels. We identified an interaction between HMGCR and a locus near LIPC in their effect on high-density lipoprotein cholesterol (HDL-C) and another pair of loci that interact in their effect on low-density lipoprotein cholesterol (LDL-C). We validated the interaction on HDL-C in a number of independent multiple-ethnic populations, while the interaction underlying LDL-C did not validate. The prior knowledge-driven searching approach and a locus-based validation procedure show the potential for dissecting and validating gene–gene interactions in current and future GWAS.
PMCID: PMC3359971  PMID: 22654671
5.  Systematic evaluation of coding variation identifies a candidate causal variant in TM6SF2 influencing total cholesterol and myocardial infarction risk 
Nature genetics  2014;46(4):345-351.
Blood lipid levels are heritable, treatable risk factors for cardiovascular disease. We systematically assessed genome-wide coding variation to identify novel lipid genes, fine-map known lipid loci, and evaluate whether low frequency variants with large effect exist. Using an exome array, we genotyped 80,137 coding variants in 5,643 Norwegians. We followed up 18 variants in 4,666 Norwegians to identify 10 loci with coding variants associated with a lipid trait (P < 5×10−8). One coding variant in TM6SF2 (p.Glu167Lys), residing in a GWAS locus for lipid levels, modifies total cholesterol levels and is associated with myocardial infarction. Transient overexpression and knockdown of TM6SF2 in mouse produces alteration in serum lipid profiles consistent with the association observed in humans, identifying TM6SF2 as the functional gene at a large GWAS locus previously known as NCAN/CILP2/PBX4 or 19p13. This study demonstrates that systematic assessment of coding variation can quickly point to a candidate causal gene.
PMCID: PMC4169222  PMID: 24633158
6.  RNAi–Based Functional Profiling of Loci from Blood Lipid Genome-Wide Association Studies Identifies Genes with Cholesterol-Regulatory Function 
PLoS Genetics  2013;9(2):e1003338.
Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease. However, GWAS only rarely reveal information on the exact genetic elements and pathogenic events underlying an association. In order to extract functional information from genomic data, strategies for systematic follow-up studies on a phenotypic level are required. Here we address these limitations by applying RNA interference (RNAi) to analyze 133 candidate genes within 56 loci identified by GWAS as associated with blood lipid levels, coronary artery disease, and/or myocardial infarction for a function in regulating cholesterol levels in cells. Knockdown of a surprisingly high number (41%) of trait-associated genes affected low-density lipoprotein (LDL) internalization and/or cellular levels of free cholesterol. Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions. Using a set of secondary assays we demonstrate for a number of genes without previously known lipid-regulatory roles (e.g. CXCL12, FAM174A, PAFAH1B1, SEZ6L, TBL2, WDR12) that knockdown correlates with altered LDL–receptor levels and/or that overexpression as GFP–tagged fusion proteins inversely modifies cellular cholesterol levels. By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.
Author Summary
Complex traits and diseases are assumed to result from interactions between multiple genes in relevant biological processes. Recent genome-wide association studies have uncovered many novel genomic loci where genes with functional significance are expected. However, functional validation of such genes has thus far remained confined to single gene approaches. Here, we use RNA interference and high-content screening microscopy to profile 133 genes at 56 loci associated with blood lipid traits, cardiovascular disease, and/or myocardial infarction for a function in regulating cellular free cholesterol levels and the efficiency of low-density lipoprotein uptake. Our results suggest that a high number of trait-associated genes have conserved cholesterol-regulatory functions in cells, with several GWAS loci harboring more than one gene of likely functional significance. For a number of genes without previously known lipid-regulatory functions, consequences upon siRNA knockdown positively correlated with cellular levels of LDL receptor, a major determinant of blood LDL levels. Moreover, GFP–tagged fusion proteins of several candidates shifted cellular cholesterol levels to inverse directions than knockdown, and subcellular localization of some candidates was sterol-dependent. Our study generates a valuable resource for prioritization of lipid-trait/CAD/MI-associated genes for future in-depth mechanistic analyses and introduces cell-based RNAi as a scalable and unbiased tool for functional follow-up of GWAS loci.
PMCID: PMC3585126  PMID: 23468663
7.  Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution 
Lindgren, Cecilia M. | Heid, Iris M. | Randall, Joshua C. | Lamina, Claudia | Steinthorsdottir, Valgerdur | Qi, Lu | Speliotes, Elizabeth K. | Thorleifsson, Gudmar | Willer, Cristen J. | Herrera, Blanca M. | Jackson, Anne U. | Lim, Noha | Scheet, Paul | Soranzo, Nicole | Amin, Najaf | Aulchenko, Yurii S. | Chambers, John C. | Drong, Alexander | Luan, Jian'an | Lyon, Helen N. | Rivadeneira, Fernando | Sanna, Serena | Timpson, Nicholas J. | Zillikens, M. Carola | Zhao, Jing Hua | Almgren, Peter | Bandinelli, Stefania | Bennett, Amanda J. | Bergman, Richard N. | Bonnycastle, Lori L. | Bumpstead, Suzannah J. | Chanock, Stephen J. | Cherkas, Lynn | Chines, Peter | Coin, Lachlan | Cooper, Cyrus | Crawford, Gabriel | Doering, Angela | Dominiczak, Anna | Doney, Alex S. F. | Ebrahim, Shah | Elliott, Paul | Erdos, Michael R. | Estrada, Karol | Ferrucci, Luigi | Fischer, Guido | Forouhi, Nita G. | Gieger, Christian | Grallert, Harald | Groves, Christopher J. | Grundy, Scott | Guiducci, Candace | Hadley, David | Hamsten, Anders | Havulinna, Aki S. | Hofman, Albert | Holle, Rolf | Holloway, John W. | Illig, Thomas | Isomaa, Bo | Jacobs, Leonie C. | Jameson, Karen | Jousilahti, Pekka | Karpe, Fredrik | Kuusisto, Johanna | Laitinen, Jaana | Lathrop, G. Mark | Lawlor, Debbie A. | Mangino, Massimo | McArdle, Wendy L. | Meitinger, Thomas | Morken, Mario A. | Morris, Andrew P. | Munroe, Patricia | Narisu, Narisu | Nordström, Anna | Nordström, Peter | Oostra, Ben A. | Palmer, Colin N. A. | Payne, Felicity | Peden, John F. | Prokopenko, Inga | Renström, Frida | Ruokonen, Aimo | Salomaa, Veikko | Sandhu, Manjinder S. | Scott, Laura J. | Scuteri, Angelo | Silander, Kaisa | Song, Kijoung | Yuan, Xin | Stringham, Heather M. | Swift, Amy J. | Tuomi, Tiinamaija | Uda, Manuela | Vollenweider, Peter | Waeber, Gerard | Wallace, Chris | Walters, G. Bragi | Weedon, Michael N. | Witteman, Jacqueline C. M. | Zhang, Cuilin | Zhang, Weihua | Caulfield, Mark J. | Collins, Francis S. | Davey Smith, George | Day, Ian N. M. | Franks, Paul W. | Hattersley, Andrew T. | Hu, Frank B. | Jarvelin, Marjo-Riitta | Kong, Augustine | Kooner, Jaspal S. | Laakso, Markku | Lakatta, Edward | Mooser, Vincent | Morris, Andrew D. | Peltonen, Leena | Samani, Nilesh J. | Spector, Timothy D. | Strachan, David P. | Tanaka, Toshiko | Tuomilehto, Jaakko | Uitterlinden, André G. | van Duijn, Cornelia M. | Wareham, Nicholas J. | Watkins for the PROCARDIS consortia, Hugh | Waterworth, Dawn M. | Boehnke, Michael | Deloukas, Panos | Groop, Leif | Hunter, David J. | Thorsteinsdottir, Unnur | Schlessinger, David | Wichmann, H.-Erich | Frayling, Timothy M. | Abecasis, Gonçalo R. | Hirschhorn, Joel N. | Loos, Ruth J. F. | Stefansson, Kari | Mohlke, Karen L. | Barroso, Inês | McCarthy for the GIANT consortium, Mark I.
PLoS Genetics  2009;5(6):e1000508.
To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×10−11) and MSRA (WC, P = 8.9×10−9). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×10−8). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
Author Summary
Here, we describe a meta-analysis of genome-wide association data from 38,580 individuals, followed by large-scale replication (in up to 70,689 individuals) designed to uncover variants influencing anthropometric measures of central obesity and fat distribution, namely waist circumference (WC) and waist–hip ratio (WHR). This work complements parallel efforts that have been successful in defining variants impacting overall adiposity and focuses on the visceral fat accumulation which has particularly strong relationships to metabolic and cardiovascular disease. Our analyses have identified two loci (TFAP2B and MSRA) associated with WC, and a further locus, near LYPLAL1, which shows gender-specific relationships with WHR (all to levels of genome-wide significance). These loci vary in the strength of their associations with overall adiposity, and LYPLAL1 in particular appears to have a specific effect on patterns of fat distribution. All in all, these three loci provide novel insights into human physiology and the development of obesity.
PMCID: PMC2695778  PMID: 19557161
8.  Genetic architecture of circulating lipid levels 
Serum concentrations of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TGs) and total cholesterol (TC) are important heritable risk factors for cardiovascular disease. Although genome-wide association studies (GWASs) of circulating lipid levels have identified numerous loci, a substantial portion of the heritability of these traits remains unexplained. Evidence of unexplained genetic variance can be detected by combining multiple independent markers into additive genetic risk scores. Such polygenic scores, constructed using results from the ENGAGE Consortium GWAS on serum lipids, were applied to predict lipid levels in an independent population-based study, the Rotterdam Study-II (RS-II). We additionally tested for evidence of a shared genetic basis for different lipid phenotypes. Finally, the polygenic score approach was used to identify an alternative genome-wide significance threshold before pathway analysis and those results were compared with those based on the classical genome-wide significance threshold. Our study provides evidence suggesting that many loci influencing circulating lipid levels remain undiscovered. Cross-prediction models suggested a small overlap between the polygenic backgrounds involved in determining LDL-C, HDL-C and TG levels. Pathway analysis utilizing the best polygenic score for TC uncovered extra information compared with using only genome-wide significant loci. These results suggest that the genetic architecture of circulating lipids involves a number of undiscovered variants with very small effects, and that increasing GWAS sample sizes will enable the identification of novel variants that regulate lipid levels.
PMCID: PMC3137496  PMID: 21448234
serum lipids; polygenic; genome-wide association; polygenic score; pathway analysis
9.  Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals 
Dastani, Zari | Hivert, Marie-France | Timpson, Nicholas | Perry, John R. B. | Yuan, Xin | Scott, Robert A. | Henneman, Peter | Heid, Iris M. | Kizer, Jorge R. | Lyytikäinen, Leo-Pekka | Fuchsberger, Christian | Tanaka, Toshiko | Morris, Andrew P. | Small, Kerrin | Isaacs, Aaron | Beekman, Marian | Coassin, Stefan | Lohman, Kurt | Qi, Lu | Kanoni, Stavroula | Pankow, James S. | Uh, Hae-Won | Wu, Ying | Bidulescu, Aurelian | Rasmussen-Torvik, Laura J. | Greenwood, Celia M. T. | Ladouceur, Martin | Grimsby, Jonna | Manning, Alisa K. | Liu, Ching-Ti | Kooner, Jaspal | Mooser, Vincent E. | Vollenweider, Peter | Kapur, Karen A. | Chambers, John | Wareham, Nicholas J. | Langenberg, Claudia | Frants, Rune | Willems-vanDijk, Ko | Oostra, Ben A. | Willems, Sara M. | Lamina, Claudia | Winkler, Thomas W. | Psaty, Bruce M. | Tracy, Russell P. | Brody, Jennifer | Chen, Ida | Viikari, Jorma | Kähönen, Mika | Pramstaller, Peter P. | Evans, David M. | St. Pourcain, Beate | Sattar, Naveed | Wood, Andrew R. | Bandinelli, Stefania | Carlson, Olga D. | Egan, Josephine M. | Böhringer, Stefan | van Heemst, Diana | Kedenko, Lyudmyla | Kristiansson, Kati | Nuotio, Marja-Liisa | Loo, Britt-Marie | Harris, Tamara | Garcia, Melissa | Kanaya, Alka | Haun, Margot | Klopp, Norman | Wichmann, H.-Erich | Deloukas, Panos | Katsareli, Efi | Couper, David J. | Duncan, Bruce B. | Kloppenburg, Margreet | Adair, Linda S. | Borja, Judith B. | Wilson, James G. | Musani, Solomon | Guo, Xiuqing | Johnson, Toby | Semple, Robert | Teslovich, Tanya M. | Allison, Matthew A. | Redline, Susan | Buxbaum, Sarah G. | Mohlke, Karen L. | Meulenbelt, Ingrid | Ballantyne, Christie M. | Dedoussis, George V. | Hu, Frank B. | Liu, Yongmei | Paulweber, Bernhard | Spector, Timothy D. | Slagboom, P. Eline | Ferrucci, Luigi | Jula, Antti | Perola, Markus | Raitakari, Olli | Florez, Jose C. | Salomaa, Veikko | Eriksson, Johan G. | Frayling, Timothy M. | Hicks, Andrew A. | Lehtimäki, Terho | Smith, George Davey | Siscovick, David S. | Kronenberg, Florian | van Duijn, Cornelia | Loos, Ruth J. F. | Waterworth, Dawn M. | Meigs, James B. | Dupuis, Josee | Richards, J. Brent
PLoS Genetics  2012;8(3):e1002607.
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.
Author Summary
Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.
PMCID: PMC3315470  PMID: 22479202
10.  Genomic study in Mexicans identifies a new locus for triglycerides and refines European lipid loci 
Journal of medical genetics  2013;50(5):298-308.
The Mexican population and others with Amerindian heritage exhibit a substantial predisposition to dyslipidemias and coronary heart disease. Yet, these populations remain underinvestigated by genomic studies, and to date, no genome-wide association (GWA) studies have been reported for lipids in these rapidly expanding populations.
Methods and Findings
We performed a two-stage GWA study for hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) in Mexicans (n=4,361) and identified a novel Mexican-specific genome-wide significant locus for serum triglycerides (TGs) near the Niemann-Pick type C1 protein (NPC1) gene (P=2.43×10−08). Furthermore, three European loci for TGs (APOA5, GCKR, and LPL) and four loci for HDL-C (ABCA1, CETP, LIPC and LOC55908) reached genome-wide significance in Mexicans. We utilized cross-ethnic mapping to narrow three European TG GWA loci, APOA5, MLXIPL, and CILP2 that were wide and contained multiple candidate variants in the European scan. At the APOA5 locus, this reduced the most likely susceptibility variants to one, rs964184. Importantly, our functional analysis demonstrated a direct link between rs964184 and postprandial serum apoAV protein levels, supporting rs964184 as the causative variant underlying the European and Mexican GWA signal. Overall, 52 of the 100 reported associations from European lipid GWA meta-analysis generalized to Mexicans. However, in 82 of the 100 European GWA loci, a different variant other than the European lead/best-proxy variant had the strongest regional evidence of association in Mexicans.
This first Mexican GWA study of lipids identified a novel GWA locus for high TG levels; utilized the inter-population heterogeneity to significantly restrict three previously known European GWA signals; and surveyed whether the European lipid GWA SNPs extend to the Mexican population.
PMCID: PMC3917605  PMID: 23505323
11.  Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts 
Nature genetics  2008;41(1):47-55.
Recent genome-wide association (GWA) studies of lipids have been conducted in samples ascertained for other phenotypes, particularly diabetes. Here we report the first GWA analysis of loci affecting total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglycerides sampled randomly from 16 population-based cohorts and genotyped using mainly the Illumina HumanHap300-Duo platform. Our study included a total of 17,797-22,562 persons, aged 18-104 years and from geographic regions spanning from the Nordic countries to Southern Europe. We established 22 loci associated with serum lipid levels at a genome-wide significance level (P < 5 × 10-8), including 16 loci that were identified by previous GWA studies. The six newly identified loci in our cohort samples are ABCG5 (TC, P = 1.5 × 10-11; LDL, P = 2.6 × 10-10), TMEM57 (TC, P = 5.4 × 10-10), CTCF-PRMT8 region (HDL, P = 8.3 × 10-16), DNAH11 (LDL, P = 6.1 × 10-9), FADS3-FADS2 (TC, P = 1.5 × 10-10; LDL, P = 4.4 × 10-13) and MADD-FOLH1 region (HDL, P = 6 × 10-11). For three loci, effect sizes differed significantly by sex. Genetic risk scores based on lipid loci explain up to 4.8% of variation in lipids and were also associated with increased intima media thickness (P = 0.001) and coronary heart disease incidence (P = 0.04). The genetic risk score improves the screening of high-risk groups of dyslipidemia over classical risk factors.
PMCID: PMC2687074  PMID: 19060911
12.  Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study 
PLoS Genetics  2011;7(6):e1002138.
For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.
Author Summary
Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels are well known independent risk factors for cardiovascular disease. Lipid-associated genetic variants are being discovered in genome-wide association studies (GWAS) in samples of European descent, but an insufficient amount of data exist in other populations. Therefore, there is a strong need to characterize the effect of these GWAS–identified variants in more diverse cohorts. In this study, we selected over forty genetic loci previously associated with lipid levels and tested for replication in a large European American cohort. We also investigated if the effect of these variants generalizes to non-European descent populations, including African Americans, American Indians, and Mexican Americans/Hispanics. A majority of these GWAS–identified associations replicated in our European American cohort. However, the ability of associations to generalize across other racial/ethnic populations varied greatly, indicating that some of these GWAS–identified variants may not be functional and are more likely to be in linkage disequilibrium with the functional variant(s).
PMCID: PMC3128106  PMID: 21738485
13.  Genetic Determinants of Long-Term Changes in Blood Lipid Concentrations: 10-Year Follow-Up of the GLACIER Study 
PLoS Genetics  2014;10(6):e1004388.
Recent genome-wide meta-analyses identified 157 loci associated with cross-sectional lipid traits. Here we tested whether these loci associate (singly and in trait-specific genetic risk scores [GRS]) with longitudinal changes in total cholesterol (TC) and triglyceride (TG) levels in a population-based prospective cohort from Northern Sweden (the GLACIER Study). We sought replication in a southern Swedish cohort (the MDC Study; N = 2,943). GLACIER Study participants (N = 6,064) were genotyped with the MetaboChip array. Up to 3,495 participants had 10-yr follow-up data available in the GLACIER Study. The TC- and TG-specific GRSs were strongly associated with change in lipid levels (β = 0.02 mmol/l per effect allele per decade follow-up, P = 2.0×10−11 for TC; β = 0.02 mmol/l per effect allele per decade follow-up, P = 5.0×10−5 for TG). In individual SNP analysis, one TC locus, apolipoprotein E (APOE) rs4420638 (β = 0.12 mmol/l per effect allele per decade follow-up, P = 2.0×10−5), and two TG loci, tribbles pseudokinase 1 (TRIB1) rs2954029 (β = 0.09 mmol/l per effect allele per decade follow-up, P = 5.1×10−4) and apolipoprotein A-I (APOA1) rs6589564 (β = 0.31 mmol/l per effect allele per decade follow-up, P = 1.4×10−8), remained significantly associated with longitudinal changes for the respective traits after correction for multiple testing. An additional 12 loci were nominally associated with TC or TG changes. In replication analyses, the APOE rs4420638, TRIB1 rs2954029, and APOA1 rs6589564 associations were confirmed (P≤0.001). In summary, trait-specific GRSs are robustly associated with 10-yr changes in lipid levels and three individual SNPs were strongly associated with 10-yr changes in lipid levels.
Author Summary
Although large cross-sectional studies have proven highly successful in identifying gene variants related to lipid levels and other cardiometabolic traits, very few examples of well-designed longitudinal studies exist where associations between genotypes and long-term changes in lipids have been assessed. Here we undertook analyses in the GLACIER Study to determine whether the 157 previously identified lipid-associated genes variants associate with changes in blood lipid levels over 10-yr follow-up. We identified a variant in APOE that is robustly associated with total cholesterol change and two variants in TRIB1 and APOA1 respectively that are robustly associated with triglyceride change. We replicated these findings in a second Swedish cohort (the MDC Study). The identified genes had previously been associated with cardiovascular traits such as myocardial infarction or coronary heart disease; hence, these novel lipid associations provide additional insight into the pathogenesis of atherosclerotic heart and large vessel disease. By incorporating all 157 established variants into gene scores, we also observed strong associations with 10-yr lipid changes, illustrating the polygenic nature of blood lipid deterioration.
PMCID: PMC4055682  PMID: 24922540
14.  A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study 
BMC Medical Genetics  2007;8(Suppl 1):S17.
Blood lipid levels including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are highly heritable. Genome-wide association is a promising approach to map genetic loci related to these heritable phenotypes.
In 1087 Framingham Heart Study Offspring cohort participants (mean age 47 years, 52% women), we conducted genome-wide analyses (Affymetrix 100K GeneChip) for fasting blood lipid traits. Total cholesterol, HDL-C, and TG were measured by standard enzymatic methods and LDL-C was calculated using the Friedewald formula. The long-term averages of up to seven measurements of LDL-C, HDL-C, and TG over a ~30 year span were the primary phenotypes. We used generalized estimating equations (GEE), family-based association tests (FBAT) and variance components linkage to investigate the relationships between SNPs (on autosomes, with minor allele frequency ≥10%, genotypic call rate ≥80%, and Hardy-Weinberg equilibrium p ≥ 0.001) and multivariable-adjusted residuals. We pursued a three-stage replication strategy of the GEE association results with 287 SNPs (P < 0.001 in Stage I) tested in Stage II (n ~1450 individuals) and 40 SNPs (P < 0.001 in joint analysis of Stages I and II) tested in Stage III (n~6650 individuals).
Long-term averages of LDL-C, HDL-C, and TG were highly heritable (h2 = 0.66, 0.69, 0.58, respectively; each P < 0.0001). Of 70,987 tests for each of the phenotypes, two SNPs had p < 10-5 in GEE results for LDL-C, four for HDL-C, and one for TG. For each multivariable-adjusted phenotype, the number of SNPs with association p < 10-4 ranged from 13 to 18 and with p < 10-3, from 94 to 149. Some results confirmed previously reported associations with candidate genes including variation in the lipoprotein lipase gene (LPL) and HDL-C and TG (rs7007797; P = 0.0005 for HDL-C and 0.002 for TG). The full set of GEE, FBAT and linkage results are posted at the database of Genotype and Phenotype (dbGaP). After three stages of replication, there was no convincing statistical evidence for association (i.e., combined P < 10-5 across all three stages) between any of the tested SNPs and lipid phenotypes.
Using a 100K genome-wide scan, we have generated a set of putative associations for common sequence variants and lipid phenotypes. Validation of selected hypotheses in additional samples did not identify any new loci underlying variability in blood lipids. Lack of replication may be due to inadequate statistical power to detect modest quantitative trait locus effects (i.e., <1% of trait variance explained) or reduced genomic coverage of the 100K array. GWAS in FHS using a denser genome-wide genotyping platform and a better-powered replication strategy may identify novel loci underlying blood lipids.
PMCID: PMC1995614  PMID: 17903299
15.  A genome-wide association study identifies a novel susceptibility locus for renal cell carcinoma on 12p11.23 
Wu, Xifeng | Scelo, Ghislaine | Purdue, Mark P. | Rothman, Nathaniel | Johansson, Mattias | Ye, Yuanqing | Wang, Zhaoming | Zelenika, Diana | Moore, Lee E. | Wood, Christopher G. | Prokhortchouk, Egor | Gaborieau, Valerie | Jacobs, Kevin B. | Chow, Wong-Ho | Toro, Jorge R. | Zaridze, David | Lin, Jie | Lubinski, Jan | Trubicka, Joanna | Szeszenia-Dabrowska, Neonilia | Lissowska, Jolanta | Rudnai, Peter | Fabianova, Eleonora | Mates, Dana | Jinga, Viorel | Bencko, Vladimir | Slamova, Alena | Holcatova, Ivana | Navratilova, Marie | Janout, Vladimir | Boffetta, Paolo | Colt, Joanne S. | Davis, Faith G. | Schwartz, Kendra L. | Banks, Rosamonde E. | Selby, Peter J. | Harnden, Patricia | Berg, Christine D. | Hsing, Ann W. | Grubb, Robert L. | Boeing, Heiner | Vineis, Paolo | Clavel-Chapelon, Françoise | Palli, Domenico | Tumino, Rosario | Krogh, Vittorio | Panico, Salvatore | Duell, Eric J. | Quirós, José Ramón | Sanchez, Maria-José | Navarro, Carmen | Ardanaz, Eva | Dorronsoro, Miren | Khaw, Kay-Tee | Allen, Naomi E. | Bueno-de-Mesquita, H. Bas | Peeters, Petra H.M. | Trichopoulos, Dimitrios | Linseisen, Jakob | Ljungberg, Börje | Overvad, Kim | Tjønneland, Anne | Romieu, Isabelle | Riboli, Elio | Stevens, Victoria L | Thun, Michael J | Diver, W. Ryan | Gapstur, Susan M. | Pharoah, Paul D. | Easton, Douglas F. | Albanes, Demetrius | Virtamo, Jarmo | Vatten, Lars | Hveem, Kristian | Fletcher, Tony | Koppova, Kvetoslava | Cussenot, Olivier | Cancel-Tassin, Geraldine | Benhamou, Simone | Hildebrandt, Michelle A. | Pu, Xia | Foglio, Mario | Lechner, Doris | Hutchinson, Amy | Yeager, Meredith | Fraumeni, Joseph F. | Lathrop, Mark | Skryabin, Konstantin G. | McKay, James D. | Gu, Jian | Brennan, Paul | Chanock, Stephen J.
Human Molecular Genetics  2011;21(2):456-462.
Renal cell carcinoma (RCC) is the most lethal urologic cancer. Only two common susceptibility loci for RCC have been confirmed to date. To identify additional RCC common susceptibility loci, we conducted an independent genome-wide association study (GWAS). We analyzed 533 191 single nucleotide polymorphisms (SNPs) for association with RCC in 894 cases and 1516 controls of European descent recruited from MD Anderson Cancer Center in the primary scan, and validated the top 500 SNPs in silico in 3772 cases and 8505 controls of European descent involved in the only published GWAS of RCC. We identified two common variants in linkage disequilibrium, rs718314 and rs1049380 (r2 = 0.64, D ′ = 0.84), in the inositol 1,4,5-triphosphate receptor, type 2 (ITPR2) gene on 12p11.23 as novel susceptibility loci for RCC (P = 8.89 × 10−10 and P = 6.07 × 10−9, respectively, in meta-analysis) with an allelic odds ratio of 1.19 [95% confidence interval (CI): 1.13–1.26] for rs718314 and 1.18 (95% CI: 1.12–1.25) for rs1049380. It has been recently identified that rs718314 in ITPR2 is associated with waist–hip ratio (WHR) phenotype. To our knowledge, this is the first genetic locus associated with both cancer risk and WHR.
PMCID: PMC3276284  PMID: 22010048
16.  Younger age of escalation of cardiovascular risk factors in Asian Indian subjects 
Cardiovascular risk factors start early, track through the young age and manifest in middle age in most societies. We conducted epidemiological studies to determine prevalence and age-specific trends in cardiovascular risk factors among adolescent and young urban Asian Indians.
Population based epidemiological studies to identify cardiovascular risk factors were performed in North India in 1999–2002. We evaluated major risk factors-smoking or tobacco use, obesity, truncal obesity, hypertension, dysglycemia and dyslipidemia using pre-specified definitions in 2051 subjects (male 1009, female 1042) aged 15–39 years of age. Age-stratified analyses were performed and significance of trends determined using regression analyses for numerical variables and Χ2 test for trend for categorical variables. Logistic regression was used to identify univariate and multivariate odds ratios (OR) for correlation of age and risk factors.
In males and females respectively, smoking or tobacco use was observed in 200 (11.8%) and 18 (1.4%), overweight or obesity (body mass index, BMI ≥ 25 kg/m2) in 12.4% and 14.3%, high waist-hip ratio, WHR (males > 0.9, females > 0.8) in 15% and 32.3%, hypertension in 5.6% and 3.1%, high LDL cholesterol (≥ 130 mg/dl) in 9.4% and 8.9%, low HDL cholesterol (<40 mg/dl males, <50 mg/dl females) in 16.2% and 49.7%, hypertriglyceridemia (≥ 150 mg/dl) in 9.7% and 6%, diabetes in 1.0% and 0.4% and the metabolic syndrome in 3.4% and 3.6%. Significantly increasing trends with age for indices of obesity (BMI, waist, WHR), glycemia (fasting glucose, metabolic syndrome) and lipids (cholesterol, LDL cholesterol, HDL cholesterol) were observed (p for trend < 0.01). At age 15–19 years the prevalence (%) of risk factors in males and females, respectively, was overweight/obesity in 7.6, 8.8; high WHR 4.9, 14.4; hypertension 2.3, 0.3; high LDL cholesterol 2.4, 3.2; high triglycerides 3.0, 3.2; low HDL cholesterol 8.0, 45.3; high total:HDL ratio 3.7, 4.7, diabetes 0.0 and metabolic syndrome in 0.0, 0.2 percent. At age groups 20–29 years in males and females, ORs were, for smoking 5.3, 1.0; obesity 1.6, 0.8; truncal obesity 4.5, 3.1; hypertension 2.6, 4.8; high LDL cholesterol 6.4, 1.8; high triglycerides 3.7, 0.9; low HDL cholesterol 2.4, 0.8; high total:HDL cholesterol 1.6, 1.0; diabetes 4.0, 1.0; and metabolic syndrome 37.7, 5.7 (p < 0.05 for some). At age 30–39, ORs were- smoking 16.0, 6.3; overweight 7.1, 11.3; truncal obesity 21.1, 17.2; hypertension 13.0, 64.0; high LDL cholesterol 27.4, 19.5; high triglycerides 24.2, 10.0; low HDL cholesterol 15.8, 14.1; high total:HDL cholesterol 37.9, 6.10; diabetes 50.7, 17.4; and metabolic syndrome 168.5, 146.2 (p < 0.01 for all parameters). Multivariate adjustment for BMI, waist size and WHR in men and women aged 30–39 years resulted in attenuation of ORs for hypertension and dyslipidemias.
Low prevalence of multiple cardiovascular risk factors (smoking, hypertension, dyslipidemias, diabetes and metabolic syndrome) in adolescents and rapid escalation of these risk factors by age of 30–39 years is noted in urban Asian Indians. Interventions should focus on these individuals.
PMCID: PMC2713196  PMID: 19575817
17.  Association of Common Genetic Variants with Lipid Traits in the Indian Population 
PLoS ONE  2014;9(7):e101688.
Genome-wide association studies (GWAS) have been instrumental in identifying novel genetic variants associated with altered plasma lipid levels. However, these quantitative trait loci have not been tested in the Indian population, where there is a poorly understood and growing burden of cardiometabolic disorders. We present the association of six single nucleotide polymorphisms in 1671 sib pairs (3342 subjects) with four lipid traits: total cholesterol, triglycerides, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C). We also investigated the interaction effects of gender, location, fat intake and physical activity. Each copy of the risk allele of rs964184 at APOA1 was associated with 1.06 mmol/l increase in triglycerides (SE = 0.049; p = 0.006), rs3764261 at CETP with 1.02 mmol/l increase in both total cholesterol (SE = 0.042; p = 0.017) and HDL-C (SE = 0.041; p = 0.008), rs646776 at CELSR2-PSRC1-SORT1 with 0.96 mmol/l decrease in cholesterol (SE = 0.043; p = 0.0003) and 0.15 mmol/l decrease in LDL-C levels (SE = 0.043; p = 0.0003) and rs2954029 at TRIB1 with 1.02 mmol/l increase in HDL-C (SE = 0.039; p = 0.047). A combined risk score of APOA1 and CETP loci predicted an increase of 1.25 mmol/l in HDL-C level (SE = 0.312; p = 0.0007). Urban location and sex had strong interaction effects on the genetic association of most of the studied loci with lipid traits. To conclude, we validated four genetic variants (identified by GWAS in western populations) associated with lipid traits in the Indian population. The interaction effects found here may explain the sex-specific differences in lipid levels and their heritability. Urbanization appears to influence the nature of the association with GWAS lipid loci in this population. However, these findings will require replication in other Indian populations.
PMCID: PMC4081649  PMID: 24991929
18.  Modeling of Environmental Effects in Genome-Wide Association Studies Identifies SLC2A2 and HP as Novel Loci Influencing Serum Cholesterol Levels 
PLoS Genetics  2010;6(1):e1000798.
Genome-wide association studies (GWAS) have identified 38 larger genetic regions affecting classical blood lipid levels without adjusting for important environmental influences. We modeled diet and physical activity in a GWAS in order to identify novel loci affecting total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels. The Swedish (SE) EUROSPAN cohort (NSE = 656) was screened for candidate genes and the non-Swedish (NS) EUROSPAN cohorts (NNS = 3,282) were used for replication. In total, 3 SNPs were associated in the Swedish sample and were replicated in the non-Swedish cohorts. While SNP rs1532624 was a replication of the previously published association between CETP and HDL cholesterol, the other two were novel findings. For the latter SNPs, the p-value for association was substantially improved by inclusion of environmental covariates: SNP rs5400 (pSE,unadjusted = 3.6×10−5, pSE,adjusted = 2.2×10−6, pNS,unadjusted = 0.047) in the SLC2A2 (Glucose transporter type 2) and rs2000999 (pSE,unadjusted = 1.1×10−3, pSE,adjusted = 3.8×10−4, pNS,unadjusted = 0.035) in the HP gene (Haptoglobin-related protein precursor). Both showed evidence of association with total cholesterol. These results demonstrate that inclusion of important environmental factors in the analysis model can reveal new genetic susceptibility loci.
Author Summary
In this article we report a genome-wide association study on cholesterol levels in the human blood. We used a Swedish cohort to select genetic polymorphisms that showed the strongest association with cholesterol levels adjusted for diet and physical activity. We replicated several genetic loci in other European cohorts. This approach extends present genome-wide association studies on lipid levels, which did not take these lifestyle factors into account, to improve statistical results and discover novel genes. In our analysis, we could identify two genetic loci in the SLC2A2 (Glucose transporter type 2) and the HP (Haptoglobin-related protein precursor) gene whose effects on total cholesterol have not been reported yet. The results show that inclusion of important environmental factors in the analysis model can reveal new insights into genetic determinants of clinical parameters relevant for metabolic and cardiovascular disease.
PMCID: PMC2792712  PMID: 20066028
19.  Biological, Clinical, and Population Relevance of 95 Loci for Blood Lipids 
Teslovich, Tanya M. | Musunuru, Kiran | Smith, Albert V. | Edmondson, Andrew C. | Stylianou, Ioannis M. | Koseki, Masahiro | Pirruccello, James P. | Ripatti, Samuli | Chasman, Daniel I. | Willer, Cristen J. | Johansen, Christopher T. | Fouchier, Sigrid W. | Isaacs, Aaron | Peloso, Gina M. | Barbalic, Maja | Ricketts, Sally L. | Bis, Joshua C. | Aulchenko, Yurii S. | Thorleifsson, Gudmar | Feitosa, Mary F. | Chambers, John | Orho-Melander, Marju | Melander, Olle | Johnson, Toby | Li, Xiaohui | Guo, Xiuqing | Li, Mingyao | Cho, Yoon Shin | Go, Min Jin | Kim, Young Jin | Lee, Jong-Young | Park, Taesung | Kim, Kyunga | Sim, Xueling | Ong, Rick Twee-Hee | Croteau-Chonka, Damien C. | Lange, Leslie A. | Smith, Joshua D. | Song, Kijoung | Zhao, Jing Hua | Yuan, Xin | Luan, Jian'an | Lamina, Claudia | Ziegler, Andreas | Zhang, Weihua | Zee, Robert Y.L. | Wright, Alan F. | Witteman, Jacqueline C.M. | Wilson, James F. | Willemsen, Gonneke | Wichmann, H-Erich | Whitfield, John B. | Waterworth, Dawn M. | Wareham, Nicholas J. | Waeber, Gérard | Vollenweider, Peter | Voight, Benjamin F. | Vitart, Veronique | Uitterlinden, Andre G. | Uda, Manuela | Tuomilehto, Jaakko | Thompson, John R. | Tanaka, Toshiko | Surakka, Ida | Stringham, Heather M. | Spector, Tim D. | Soranzo, Nicole | Smit, Johannes H. | Sinisalo, Juha | Silander, Kaisa | Sijbrands, Eric J.G. | Scuteri, Angelo | Scott, James | Schlessinger, David | Sanna, Serena | Salomaa, Veikko | Saharinen, Juha | Sabatti, Chiara | Ruokonen, Aimo | Rudan, Igor | Rose, Lynda M. | Roberts, Robert | Rieder, Mark | Psaty, Bruce M. | Pramstaller, Peter P. | Pichler, Irene | Perola, Markus | Penninx, Brenda W.J.H. | Pedersen, Nancy L. | Pattaro, Cristian | Parker, Alex N. | Pare, Guillaume | Oostra, Ben A. | O'Donnell, Christopher J. | Nieminen, Markku S. | Nickerson, Deborah A. | Montgomery, Grant W. | Meitinger, Thomas | McPherson, Ruth | McCarthy, Mark I. | McArdle, Wendy | Masson, David | Martin, Nicholas G. | Marroni, Fabio | Mangino, Massimo | Magnusson, Patrik K.E. | Lucas, Gavin | Luben, Robert | Loos, Ruth J. F. | Lokki, Maisa | Lettre, Guillaume | Langenberg, Claudia | Launer, Lenore J. | Lakatta, Edward G. | Laaksonen, Reijo | Kyvik, Kirsten O. | Kronenberg, Florian | König, Inke R. | Khaw, Kay-Tee | Kaprio, Jaakko | Kaplan, Lee M. | Johansson, Åsa | Jarvelin, Marjo-Riitta | Janssens, A. Cecile J.W. | Ingelsson, Erik | Igl, Wilmar | Hovingh, G. Kees | Hottenga, Jouke-Jan | Hofman, Albert | Hicks, Andrew A. | Hengstenberg, Christian | Heid, Iris M. | Hayward, Caroline | Havulinna, Aki S. | Hastie, Nicholas D. | Harris, Tamara B. | Haritunians, Talin | Hall, Alistair S. | Gyllensten, Ulf | Guiducci, Candace | Groop, Leif C. | Gonzalez, Elena | Gieger, Christian | Freimer, Nelson B. | Ferrucci, Luigi | Erdmann, Jeanette | Elliott, Paul | Ejebe, Kenechi G. | Döring, Angela | Dominiczak, Anna F. | Demissie, Serkalem | Deloukas, Panagiotis | de Geus, Eco J.C. | de Faire, Ulf | Crawford, Gabriel | Collins, Francis S. | Chen, Yii-der I. | Caulfield, Mark J. | Campbell, Harry | Burtt, Noel P. | Bonnycastle, Lori L. | Boomsma, Dorret I. | Boekholdt, S. Matthijs | Bergman, Richard N. | Barroso, Inês | Bandinelli, Stefania | Ballantyne, Christie M. | Assimes, Themistocles L. | Quertermous, Thomas | Altshuler, David | Seielstad, Mark | Wong, Tien Y. | Tai, E-Shyong | Feranil, Alan B. | Kuzawa, Christopher W. | Adair, Linda S. | Taylor, Herman A. | Borecki, Ingrid B. | Gabriel, Stacey B. | Wilson, James G. | Stefansson, Kari | Thorsteinsdottir, Unnur | Gudnason, Vilmundur | Krauss, Ronald M. | Mohlke, Karen L. | Ordovas, Jose M. | Munroe, Patricia B. | Kooner, Jaspal S. | Tall, Alan R. | Hegele, Robert A. | Kastelein, John J.P. | Schadt, Eric E. | Rotter, Jerome I. | Boerwinkle, Eric | Strachan, David P. | Mooser, Vincent | Holm, Hilma | Reilly, Muredach P. | Samani, Nilesh J | Schunkert, Heribert | Cupples, L. Adrienne | Sandhu, Manjinder S. | Ridker, Paul M | Rader, Daniel J. | van Duijn, Cornelia M. | Peltonen, Leena | Abecasis, Gonçalo R. | Boehnke, Michael | Kathiresan, Sekar
Nature  2010;466(7307):707-713.
Serum concentrations of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with serum lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 × 10-8), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (e.g., CYP7A1, NPC1L1, and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and impact lipid traits in three non-European populations (East Asians, South Asians, and African Americans). Our results identify several novel loci associated with serum lipids that are also associated with CAD. Finally, we validated three of the novel genes—GALNT2, PPP1R3B, and TTC39B—with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
PMCID: PMC3039276  PMID: 20686565
20.  Links between cardiovascular disease and osteoporosis in postmenopausal women: serum lipids or atherosclerosis per se? 
Osteoporosis International  2006;18(4):505-512.
Introduction and hypothesis
Epidemiological observations suggest links between osteoporosis and risk of acute cardiovascular events and vice versa. Whether the two clinical conditions are linked by common pathogenic factors or atherosclerosis per se remains incompletely understood. We investigated whether serum lipids and polymorphism in the ApoE gene modifying serum lipids could be a biological linkage.
This was an observational study including 1176 elderly women 60–85 years old. Women were genotyped for epsilon (ɛ) allelic variants of the ApoE gene, and data concerning serum lipids (total cholesterol, triglycerides, HDL-C, LDL-C, apoA1, ApoB, Lp(a)), hip and spine BMD, aorta calcification (AC), radiographic vertebral fracture and self-reported wrist and hip fractures, cardiovascular events together with a wide array of demographic and lifestyle characteristics were collected.
Presence of the ApoE ɛ4 allele had a significant impact on serum lipid profile, yet no association with spine/hip BMD or AC could be established. In multiple regression models, apoA1 was a significant independent contributor to the variation in AC. However, none of the lipid components were independent contributors to the variation in spine or hip BMD. When comparing the women with or without vertebral fractures, serum triglycerides showed significant differences. This finding was however not applicable to hip or wrist fractures. After adjustment for age, severe AC score (≥6) and/or manifest cardiovascular disease increased the risk of hip but not vertebral or wrist fractures.
The contribution of serum lipids to the modulators of BMD does not seem to be direct but rather indirect via promotion of atherosclerosis, which in turn can affect bone metabolism locally, especially when skeletal sites supplied by end-arteries are concerned. Further studies are needed to explore the genetic or environmental risk factors underlying the association of low triglyceride levels to vertebral fractures.
PMCID: PMC1820757  PMID: 17109061
Aorta calcification; ApoE polymorphism; Cardiovascular events; Lipids; Osteoporosis
21.  Genome Wide Meta-analysis Highlights the Role of Genetic Variation in RARRES2 in the Regulation of Circulating Serum Chemerin 
PLoS Genetics  2014;10(12):e1004854.
Chemerin is an adipokine proposed to link obesity and chronic inflammation of adipose tissue. Genetic factors determining chemerin release from adipose tissue are yet unknown. We conducted a meta-analysis of genome-wide association studies (GWAS) for serum chemerin in three independent cohorts from Europe: Sorbs and KORA from Germany and PPP-Botnia from Finland (total N = 2,791). In addition, we measured mRNA expression of genes within the associated loci in peripheral mononuclear cells by micro-arrays, and within adipose tissue by quantitative RT-PCR and performed mRNA expression quantitative trait and expression-chemerin association studies to functionally substantiate our loci. Heritability estimate of circulating chemerin levels was 16.2% in the Sorbs cohort. Thirty single nucleotide polymorphisms (SNPs) at chromosome 7 within the retinoic acid receptor responder 2 (RARRES2)/Leucine Rich Repeat Containing (LRRC61) locus reached genome-wide significance (p<5.0×10−8) in the meta-analysis (the strongest evidence for association at rs7806429 with p = 7.8×10−14, beta = −0.067, explained variance 2.0%). All other SNPs within the cluster were in linkage disequilibrium with rs7806429 (minimum r2 = 0.43 in the Sorbs cohort). The results of the subgroup analyses of males and females were consistent with the results found in the total cohort. No significant SNP-sex interaction was observed. rs7806429 was associated with mRNA expression of RARRES2 in visceral adipose tissue in women (p<0.05 after adjusting for age and body mass index). In conclusion, the present meta-GWAS combined with mRNA expression studies highlights the role of genetic variation in the RARRES2 locus in the regulation of circulating chemerin concentrations.
Author Summary
Chemerin is an adipokine proposed to link obesity and chronic inflammation of adipose tissue. In the present study we show that circulating chemerin is a heritable trait. In a meta-analysis of genome-wide association studies (GWAS) of 2,791 individuals from Germany and Finland, we identified common genetic variants which associate with serum chemerin levels. The variants map within the retinoic acid receptor responder 2 (RARRES2)/Leucine Rich Repeat Containing (LRRC61) at chromosome 7. To better understand the potential functionality of the identified variants, we also provide insights into the mRNA expression of RARRES2 (encoding chemerin) in blood and adipose tissue. Our results highlight the role and function of genetic variation in the RARRES2 locus in the regulation of circulating chemerin concentrations.
PMCID: PMC4270463  PMID: 25521368
22.  Heritability and genome-wide association analysis of renal sinus fat accumulation in the Framingham Heart Study 
BMC Medical Genetics  2011;12:148.
Ectopic fat accumulation in the renal sinus is associated with chronic kidney disease and hypertension. The genetic contributions to renal sinus fat accumulation in humans have not been well characterized.
The present analysis consists of participants from the Framingham Offspring and Third Generation who underwent computed tomography; renal sinus fat and visceral adipose tissue (VAT) were quantified. Renal sinus fat was natural log transformed and sex- and cohort-specific residuals were created, adjusted for (1) age, (2) age and body mass index (BMI), and (3) age and VAT. Residuals were pooled and used to calculate heritability using variance-components analysis in SOLAR. A genome-wide association study (GWAS) for renal sinus fat was performed using an additive model with approximately 2.5 million imputed single nucleotide polymorphisms (SNPs). Finally, we identified the associations of renal sinus fat in our GWAS results with validated SNPs for renal function (n = 16), BMI (n = 32), and waist-to-hip ratio (WHR, n = 14), and applied a multi-SNP genetic risk score method to determine if the SNPs for each renal and obesity trait were in aggregate associated with renal sinus fat.
The heritability of renal sinus fat was 39% (p < 0.0001); results were not materially different after adjustment for BMI (39%) or VAT (40%). No SNPs reached genome-wide significance in our GWAS. In our candidate gene analysis, we observed nominal, direction consistent associations with renal sinus fat for one SNP associated with renal function (p = 0.01), two associated with BMI (p < 0.03), and two associated with WHR (p < 0.03); however, none remained significant after accounting for multiple testing. Finally, we observed that in aggregate, the 32 SNPs associated with BMI were nominally associated with renal sinus fat (multi-SNP genetic risk score p = 0.03).
Renal sinus fat is a heritable trait, even after accounting for generalized and abdominal adiposity. This provides support for further research into the genetic determinants of renal sinus fat. While our study was underpowered to detect genome-wide significant loci, our candidate gene BMI risk score results suggest that variability in renal sinus fat may be associated with SNPs previously known to be associated with generalized adiposity.
PMCID: PMC3243045  PMID: 22044751
23.  Variation in the UCP2 and UCP3 genes associates with abdominal obesity and serum lipids: The Finnish Diabetes Prevention Study 
BMC Medical Genetics  2009;10:94.
We explored the associations of three variants in the uncoupling protein 2 (UCP2) gene, one variant in the UCP2-UCP3 intergenic region and five variants in the uncoupling protein 3 (UCP3) gene with obesity and diabetes related traits in subjects with impaired glucose tolerance participating in Finnish Diabetes Prevention Study. Altogether 507 overweight individuals (body mass index: 31.2 ± 4.5 kg/m2, age: 55 ± 7 years) for whom DNA was available were randomized to either an intensified diet and physical activity group or to a conventional care control group.
We analysed the data from the baseline and annual follow-up visits from years 1, 2 and 3. Measurements of anthropometry, plasma glucose and serum insulin in oral glucose tolerance test, serum total cholesterol, HDL-cholesterol and triglycerides were included. The median follow-up time for type 2 diabetes incidence was 7 years. Genetic variants were screened by restriction fragment length polymorphism or Illumina method.
UCP3 gene variant rs3781907 was associated with increased serum total and LDL-cholesterol levels, at baseline and during the follow-up period. The same variant was associated with a higher risk of type 2 diabetes. Variants rs1726745, rs11235972 and rs1800849 in the UCP3 gene associated with serum total and LDL-cholesterol at baseline. Haploblock including variants rs659366, rs653529, rs15763, and rs1726745 was associated with measures of abdominal obesity at baseline and in the longitudinal analysis. The haplotype comprising alleles rs659366-G, rs653529-A, rs15763-G and rs1726745-A was associated with higher waist-to-hip ratio, and haplotype comprising alleles rs3781907-G, rs11235972-A, and rs1800849-T was associated with increased serum total and LDL-cholesterol concentrations.
Genetic variation in the UCP2-UCP3 gene cluster may act as a modifier increasing serum lipid levels and indices of abdominal obesity, and may thereby also contribute to the metabolic aberrations observed in obesity and type 2 diabetes.
PMCID: PMC2754982  PMID: 19769793
24.  Insight in Genome-Wide Association of Metabolite Quantitative Traits by Exome Sequence Analyses 
PLoS Genetics  2015;11(1):e1004835.
Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10−32), PRODH with proline (P-value  = 1.11×10−19), SLC16A9 with carnitine level (P-value  = 4.81×10−14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10−19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10−8), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10−8) and 2p12 locus with valine (P-value  = 3.49×10−8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.
Author Summary
Human metabolic individuality is under strict control of genetic and environmental factors. In our study, we aimed to find the genetic determinants of circulating molecules in sera of large set of individuals representing the general population. First, we performed a hypothesis-free genome wide screen in this population to identify genetic regions of interest. Our study confirmed four known gene metabolite connections, but also pointed to four novel ones. Genome-wide screens enriched for common intergenic variants may miss causal genetic variations directly changing the protein sequence. To investigate this further, we zoomed into regions of interest and tested whether the association signals obtained in the first stage were direct, or whether they represent causal variations, which were not captured in the initial panel. These subsequent tests showed that protein coding and regulatory variations are involved in metabolite levels. For two genomic regions we also found that genes harbour more than one causal variant influencing metabolite levels independent of each other. We also observed strong connection between markers of cardio-metabolic health and metabolites. Taken together, our novel loci are of interest for further research to investigate the causal relation to for instance type 2 diabetes and cardiovascular disease.
PMCID: PMC4287344  PMID: 25569235
25.  Fine Mapping of Five Loci Associated with Low-Density Lipoprotein Cholesterol Detects Variants That Double the Explained Heritability 
PLoS Genetics  2011;7(7):e1002198.
Complex trait genome-wide association studies (GWAS) provide an efficient strategy for evaluating large numbers of common variants in large numbers of individuals and for identifying trait-associated variants. Nevertheless, GWAS often leave much of the trait heritability unexplained. We hypothesized that some of this unexplained heritability might be due to common and rare variants that reside in GWAS identified loci but lack appropriate proxies in modern genotyping arrays. To assess this hypothesis, we re-examined 7 genes (APOE, APOC1, APOC2, SORT1, LDLR, APOB, and PCSK9) in 5 loci associated with low-density lipoprotein cholesterol (LDL-C) in multiple GWAS. For each gene, we first catalogued genetic variation by re-sequencing 256 Sardinian individuals with extreme LDL-C values. Next, we genotyped variants identified by us and by the 1000 Genomes Project (totaling 3,277 SNPs) in 5,524 volunteers. We found that in one locus (PCSK9) the GWAS signal could be explained by a previously described low-frequency variant and that in three loci (PCSK9, APOE, and LDLR) there were additional variants independently associated with LDL-C, including a novel and rare LDLR variant that seems specific to Sardinians. Overall, this more detailed assessment of SNP variation in these loci increased estimates of the heritability of LDL-C accounted for by these genes from 3.1% to 6.5%. All association signals and the heritability estimates were successfully confirmed in a sample of ∼10,000 Finnish and Norwegian individuals. Our results thus suggest that focusing on variants accessible via GWAS can lead to clear underestimates of the trait heritability explained by a set of loci. Further, our results suggest that, as prelude to large-scale sequencing efforts, targeted re-sequencing efforts paired with large-scale genotyping will increase estimates of complex trait heritability explained by known loci.
Author Summary
Despite the striking success of genome-wide association studies in identifying genetic loci associated with common complex traits and diseases, much of the heritable risk for these traits and diseases remains unexplained. A higher resolution investigation of the genome through sequencing studies is expected to clarify the sources of this missing heritability. As a preview of what we might learn in these more detailed assessments of genetic variation, we used sequencing to identify potentially interesting variants in seven genes associated with low-density lipoprotein cholesterol (LDL-C) in 256 Sardinian individuals with extreme LDL-C levels, followed by large scale genotyping in 5,524 individuals, to examine newly discovered and previously described variants. We found that a combination of common and rare variants in these loci contributes to variation in LDL-C levels, and also that the initial estimate of the heritability explained by these loci doubled. Importantly, our results include a Sardinian-specific rare variant, highlighting the need for sequencing studies in isolated populations. Our results provide insights about what extensive whole-genome sequencing efforts are likely to reveal for the understanding of the genetic architecture of complex traits.
PMCID: PMC3145627  PMID: 21829380

Results 1-25 (986546)