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1.  Genes implicated in serotonergic and dopaminergic functioning predict BMI categories 
Obesity (Silver Spring, Md.)  2008;16(2):348-355.
Objective
This study addressed the hypothesis that variation in genes associated with dopamine function (SLC6A3, DRD2, DRD4), serotonin function (SLC6A4), and regulation of monoamine levels (MAOA) may be predictive of BMI categories (obese and overweight + obese) in young adulthood and of changes in BMI as adolescents transition into young adulthood. Interactions with gender and race/ethnicity were also examined.
Research Methods and Procedures
Participants were a subsample of individuals from The National Longitudinal Study of Adolescent Health (Add Health), a nationally representative sample of adolescents followed from 1995 to 2002. The sample analyzed included a subset of 1584 unrelated individuals with genotype data. Multiple logistic regressions were conducted to evaluate associations between genotypes and obesity (BMI > 29.9) or overweight + obese combined (BMI > 25) with normal weight (BMI = 18.5–24.9) as a referent. Linear regression models were used examine change in BMI from adolescence to young adulthood.
Results
Significant associations were found between SLC6A4 5HTTLPR and categories of BMI, and between MAOA promoter VNTR among males and categories of BMI. Stratified analyses revealed that the association between these two genes and excess BMI was significant for males overall, and for White and Hispanic males specifically. Linear regression models indicated a significant effect of SLC6A4 5HTTLPR on change in BMI from adolescence to young adulthood.
Discussion
Our findings lend further support to the involvement of genes implicated in dopamine and serotonin regulation on energy balance.
doi:10.1038/oby.2007.65
PMCID: PMC2919156  PMID: 18239643
Adolescents; Genetic Epidemiology; Serotonin; Neuro Transmitter
2.  Association of Obesity with cardiovascular disease mortality in the PLCO trial 
Preventive medicine  2013;57(1):60-64.
Background
Obesity is a risk factor for cardiovascular disease (CVD) mortality, but the association between obesity and specific causes of CVD mortality are still under investigation.
Method
We prospectively examined body-mass index (BMI) in relation to CVD-specific causes of death in approximately 86,000 US men and women in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, followed for up to 13 years. BMI was calculated from self-reported weight and height at baseline. Hazard ratios (HRs) were calculated overall and stratified by sex, smoking status, and educational level.
Result
Overweight non-obese participants (BMI: 25.0–29.9) were not at excess risk for CVD mortality (HR and CIs are 1.02 [0.92–1.13], compared to participants of normal BMI (18.5–24.9). Excess CVD mortality was observed for participants of BMI 30.0–34.9 (HR and CIs: 1.29 [1.13–1.48], BMI 35.0–39.9 (HR and CIs: 1.87 [1.51–2.32]) and BMI 40.0+ (HR and CIs: 2.21 [1.57–3.21]) (p<0.001 for trend). BMI was unrelated to mortality due to stroke. The observed association of BMI with CVD was independent of gender, smoking status and educational level.
Conclusion
Obesity is associated with increased mortality due to CVD.
doi:10.1016/j.ypmed.2013.04.014
PMCID: PMC3674167  PMID: 23632233
3.  Functional Genomics of Attention-Deficit/ Hyperactivity Disorder (ADHD) Risk Alleles on Dopamine Transporter Binding in ADHD and Healthy Control Subjects 
Biological psychiatry  2012;74(2):84-89.
Background
The main aim of this study was to examine the relationship between dopamine transporter (DAT) binding in the striatum in individuals with and without attention-deficit/hyperactivity disorder (ADHD), attending to the 3′-untranslated region of the gene (3′-UTR) and intron8 variable number of tandem repeats (VNTR) polymorphisms of the DAT (SLC6A3) gene.
Methods
Subjects consisted of 68 psychotropic (including stimulant)-naïve and smoking-naïve volunteers between 18 and 55 years of age (ADHD n = 34; control subjects n = 34). Striatal DAT binding was measured with positron emission tomography with 11C altropane. Genotyping of the two DAT (SLC6A3) 3′-UTR and intron8 VNTRs used standard protocols.
Results
The gene frequencies of each of the gene polymorphisms assessed did not differ between the ADHD and control groups. The ADHD status (t = 2.99; p < .004) and 3′-UTR of SLC6A3 9 repeat carrier status (t = 2.74; p < .008) were independently and additively associated with increased DAT binding in the caudate. The ADHD status was associated with increased striatal (caudate) DAT binding regardless of 3′-UTR genotype, and 3′-UTR genotype was associated with increased striatal (caudate) DAT binding regardless of ADHD status. In contrast, there were no significant associations between polymorphisms of DAT intron8 or the 3′-UTR-intron8 haplotype with DAT binding.
Conclusions
The 3′-UTR but not intron8 VNTR genotypes were associated with increased DAT binding in both ADHD patients and healthy control subjects. Both ADHD status and the 3′-UTR polymorphism status had an additive effect on DAT binding. Our findings suggest that an ADHD risk polymorphism (3′-UTR) of SLC6A3 has functional consequences on central nervous system DAT binding in humans.
doi:10.1016/j.biopsych.2012.11.010
PMCID: PMC3700607  PMID: 23273726
ADHD; altropane; dopamine; dopamine transporter; genetics; PET imaging
4.  Evaluation of the Lung Cancer Risks at Which to Screen Ever- and Never-Smokers: Screening Rules Applied to the PLCO and NLST Cohorts 
PLoS Medicine  2014;11(12):e1001764.
Martin Tammemägi and colleagues evaluate which risk groups of individuals, including nonsmokers and high-risk individuals from 65 to 80 years of age, should be screened for lung cancer using computed tomography.
Please see later in the article for the Editors' Summary
Background
Lung cancer risks at which individuals should be screened with computed tomography (CT) for lung cancer are undecided. This study's objectives are to identify a risk threshold for selecting individuals for screening, to compare its efficiency with the U.S. Preventive Services Task Force (USPSTF) criteria for identifying screenees, and to determine whether never-smokers should be screened. Lung cancer risks are compared between smokers aged 55–64 and ≥65–80 y.
Methods and Findings
Applying the PLCOm2012 model, a model based on 6-y lung cancer incidence, we identified the risk threshold above which National Lung Screening Trial (NLST, n = 53,452) CT arm lung cancer mortality rates were consistently lower than rates in the chest X-ray (CXR) arm. We evaluated the USPSTF and PLCOm2012 risk criteria in intervention arm (CXR) smokers (n = 37,327) of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). The numbers of smokers selected for screening, and the sensitivities, specificities, and positive predictive values (PPVs) for identifying lung cancers were assessed. A modified model (PLCOall2014) evaluated risks in never-smokers. At PLCOm2012 risk ≥0.0151, the 65th percentile of risk, the NLST CT arm mortality rates are consistently below the CXR arm's rates. The number needed to screen to prevent one lung cancer death in the 65th to 100th percentile risk group is 255 (95% CI 143 to 1,184), and in the 30th to <65th percentile risk group is 963 (95% CI 291 to −754); the number needed to screen could not be estimated in the <30th percentile risk group because of absence of lung cancer deaths. When applied to PLCO intervention arm smokers, compared to the USPSTF criteria, the PLCOm2012 risk ≥0.0151 threshold selected 8.8% fewer individuals for screening (p<0.001) but identified 12.4% more lung cancers (sensitivity 80.1% [95% CI 76.8%–83.0%] versus 71.2% [95% CI 67.6%–74.6%], p<0.001), had fewer false-positives (specificity 66.2% [95% CI 65.7%–66.7%] versus 62.7% [95% CI 62.2%–63.1%], p<0.001), and had higher PPV (4.2% [95% CI 3.9%–4.6%] versus 3.4% [95% CI 3.1%–3.7%], p<0.001). In total, 26% of individuals selected for screening based on USPSTF criteria had risks below the threshold PLCOm2012 risk ≥0.0151. Of PLCO former smokers with quit time >15 y, 8.5% had PLCOm2012 risk ≥0.0151. None of 65,711 PLCO never-smokers had PLCOm2012 risk ≥0.0151. Risks and lung cancers were significantly greater in PLCO smokers aged ≥65–80 y than in those aged 55–64 y. This study omitted cost-effectiveness analysis.
Conclusions
The USPSTF criteria for CT screening include some low-risk individuals and exclude some high-risk individuals. Use of the PLCOm2012 risk ≥0.0151 criterion can improve screening efficiency. Currently, never-smokers should not be screened. Smokers aged ≥65–80 y are a high-risk group who may benefit from screening.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Lung cancer is the most commonly occurring cancer in the world and the most common cause of cancer-related deaths. Like all cancers, lung cancer occurs when cells acquire genetic changes that allow them to grow uncontrollably and to move around the body (metastasize). The most common trigger for these genetic changes in lung cancer is exposure to cigarette smoke. Symptoms of lung cancer include a persistent cough and breathlessness. If lung cancer is diagnosed when it is confined to the lung (stage I), the tumor can often be removed surgically. Stage II tumors, which have spread into nearby lymph nodes, are usually treated with surgery plus chemotherapy or radiotherapy. For more advanced lung cancers that have spread throughout the chest (stage III) or the body (stage IV), surgery is rarely helpful and these tumors are treated with chemotherapy and radiotherapy alone. Overall, because most lung cancers are not detected until they are advanced, less than 17% of people diagnosed with lung cancer survive for five years.
Why Was This Study Done?
Screening for lung cancer—looking for early disease in healthy people—could save lives. In the US National Lung Screening Trial (NLST), annual screening with computed tomography (CT) reduced lung cancer mortality by 20% among smokers at high risk of developing cancer compared with screening with a chest X-ray. But what criteria should be used to decide who is screened for lung cancer? The US Preventive Services Task Force (USPSTF), for example, recommends annual CT screening of people who are 55–80 years old, have smoked 30 or more pack-years (one pack-year is defined as a pack of cigarettes per day for one year), and—if they are former smokers—quit smoking less than 15 years ago. However, some experts think lung cancer risk prediction models—statistical models that estimate risk based on numerous personal characteristics—should be used to select people for screening. Here, the researchers evaluate PLCOm2012, a lung cancer risk prediction model based on the incidence of lung cancer among smokers enrolled in the US Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). Specifically, the researchers use NLST and PLCO screening trial data to identify a PLCOm2012 risk threshold for selecting people for screening and to compare the efficiency of the PLCOm2012 model and the USPSTF criteria for identifying “screenees.”
What Did the Researchers Do and Find?
By analyzing NLST data, the researchers calculated that at PLCOm2012 risk ≥0.0151, mortality (death) rates among NLST participants screened with CT were consistently below mortality rates among NLST participants screened with chest X-ray and that 255 people with a PLCOm2012 risk ≥0.0151 would need to be screened to prevent one lung cancer death. Next, they used data collected from smokers in the screened arm of the PLCO trial to compare the efficiency of the PLCOm2012 and USPSTF criteria for identifying screenees. They found that 8.8% fewer people had a PLCOm2012 risk ≥0.0151 than met USPSTF criteria for screening, but 12.4% more lung cancers were identified. Thus, using PLCOm2012 improved the sensitivity and specificity of the selection of individuals for lung cancer screening over using UPSTF criteria. Notably, 8.5% of PLCO former smokers with quit times of more than 15 years had PLCOm2012 risk ≥0.0151, none of the PLCO never-smokers had PLCOm2012 risk ≥0.0151, and the calculated risks and incidence of lung cancer were greater among PLCO smokers aged ≥65–80 years than among those aged 55–64 years.
What Do These Findings Mean?
Despite the absence of a cost-effectiveness analysis in this study, these findings suggest that the use of the PLCOm2012 risk ≥0.0151 threshold rather than USPSTF criteria for selecting individuals for lung cancer screening could improve screening efficiency. The findings have several other important implications. First, these findings suggest that screening may be justified in people who stopped smoking more than 15 years ago; USPSTF currently recommends that screening stop once an individual's quit time exceeds 15 years. Second, these findings do not support lung cancer screening among never-smokers. Finally, these findings suggest that smokers aged ≥65–80 years might benefit from screening, although the presence of additional illnesses and reduced life expectancy need to be considered before recommending the provision of routine lung cancer screening to this section of the population.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001764.
The US National Cancer Institute provides information about all aspects of lung cancer for patients and health-care professionals, including information on lung cancer screening (in English and Spanish)
Cancer Research UK also provides detailed information about lung cancer and about lung cancer screening
The UK National Health Service Choices website has a page on lung cancer that includes personal stories
MedlinePlus provides links to other sources of information about lung cancer (in English and Spanish)
Information about the USPSTF recommendations for lung cancer screening is available
doi:10.1371/journal.pmed.1001764
PMCID: PMC4251899  PMID: 25460915
5.  Genetic Variation in Sodium-Dependent Vitamin C Transporters SLC23A1 and SLC23A2 and Risk of Advanced Colorectal Adenoma 
Nutrition and cancer  2008;60(5):652-659.
Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf
This article may be used for research, teaching and private study purposes. Any substantial orsystematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply ordistribution in any form to anyone is expressly forbidden
The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae and drug dosesshould be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directlyor indirectly in connection with or arising out of the use of this material.
Previous observational studies suggest that vitamin C may reduce risk of colorectal cancer. Vitamin C transport is facilitated by membrane bound sodium-dependent transporters, SVCT1 (encoded by SLC23A1) and SVCT2 (encoded by SLC23A2). To investigate if common genetic variants in these two genes are associated with risk of colorectal tumor development, we conducted a case-control study of 656 Caucasian advanced distal colorectal adenoma cases and 665 Caucasian sigmoidoscopy-negative controls nested within the screening arm of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. The analysis of common single nucleotide polymorphisms in SLC23A1 revealed no association. For SLC23A2, overall, there was no association with haplotypes, but two SNPs located inintron 8 and exon 11 could be associated (odds ratio = 0.49, 95% confidence interval = 0.25–0.95 for haplotype G-C vs. haplotype C-C). The findings should be confirmed in follow-up studies, and further investigation is required to probe the functional basis of this finding.
doi:10.1080/01635580802033110
PMCID: PMC3490215  PMID: 18791929
6.  Change in the Body Mass Index Distribution for Women: Analysis of Surveys from 37 Low- and Middle-Income Countries 
PLoS Medicine  2013;10(1):e1001367.
Using cross-sectional surveys, Fahad Razak and colleagues investigate how the BMI (body mass index) distribution is changing for women in low- and middle-income countries.
Background
There are well-documented global increases in mean body mass index (BMI) and prevalence of overweight (BMI≥25.0 kg/m2) and obese (BMI≥30.0 kg/m2). Previous analyses, however, have failed to report whether this weight gain is shared equally across the population. We examined the change in BMI across all segments of the BMI distribution in a wide range of countries, and assessed whether the BMI distribution is changing between cross-sectional surveys conducted at different time points.
Methods and Findings
We used nationally representative surveys of women between 1991–2008, in 37 low- and middle-income countries from the Demographic Health Surveys ([DHS] n = 732,784). There were a total of 96 country-survey cycles, and the number of survey cycles per country varied between two (21/37) and five (1/37). Using multilevel regression models, between countries and within countries over survey cycles, the change in mean BMI was used to predict the standard deviation of BMI, the prevalence of underweight, overweight, and obese. Changes in median BMI were used to predict the 5th and 95th percentile of the BMI distribution. Quantile-quantile plots were used to examine the change in the BMI distribution between surveys conducted at different times within countries. At the population level, increasing mean BMI is related to increasing standard deviation of BMI, with the BMI at the 95th percentile rising at approximately 2.5 times the rate of the 5th percentile. Similarly, there is an approximately 60% excess increase in prevalence of overweight and 40% excess in obese, relative to the decline in prevalence of underweight. Quantile-quantile plots demonstrate a consistent pattern of unequal weight gain across percentiles of the BMI distribution as mean BMI increases, with increased weight gain at high percentiles of the BMI distribution and little change at low percentiles. Major limitations of these results are that repeated population surveys cannot examine weight gain within an individual over time, most of the countries only had data from two surveys and the study sample only contains women in low- and middle-income countries, potentially limiting generalizability of findings.
Conclusions
Mean changes in BMI, or in single parameters such as percent overweight, do not capture the divergence in the degree of weight gain occurring between BMI at low and high percentiles. Population weight gain is occurring disproportionately among groups with already high baseline BMI levels. Studies that characterize population change should examine patterns of change across the entire distribution and not just average trends or single parameters.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The number of obese people (individuals who have an excessive amount of body fat) is rapidly increasing in many countries. Globally, there were about 200 million obese adults in 1995; by 2010, 475 million adults were obese and another billion were classified as overweight. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Compared to people with a healthy weight (a BMI between 18.5 and 24.9 kg/m2), obese individuals and overweight individuals (who have a BMI between 25.0 and 29.9 kg/m2) have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. At the same time in many developing countries substantial numbers of people are underweight (BMI <18.5 kg/m2) or have chronic energy deficiency (BMI <16.0 kg/m2) and are at risk of increased risk of dying due to infectious disease or respiratory problems.
Why Was This Study Done?
The global obesity epidemic is usually described in terms of increases in the average BMI or in the prevalence of obesity (the proportion of the population whose BMI is above 30.0 kg/m2). Such descriptions assume that the BMIs of fat and thin people are increasing at the same rate and that the shape of the population's BMI distribution curve remains constant. However, as average BMI and the prevalence of obesity can increase it is unclear how the prevalence of underweight changes. This is potentially important for the health of the population because underweight individuals, like obese individuals, tend to die younger than healthy weight individuals, particularly in low-income countries. In this study, the researchers use repeated cross-sectional survey data collected from low- and middle-income countries in the Demographic and Health Surveys (DHS) to examine changes in BMI in women across the BMI distribution between 1991 and 2008. Repeated cross-sectional surveys collect data from a population at multiple time points from different individuals drawn from the same population, DHS are a data collection and surveillance project that help developing countries track health and population trends.
What Did the Researchers Do and Find?
The researchers used statistical models to analyze data from DHS surveys of more than 730,000 women living in 37 low- and middle-income countries (two to five surveys per country). Increasing average BMI was associated with an increase in the standard deviation of BMI (a measure of the dispersion of BMI in the population) both across and within countries over time. With increasing average BMI, the BMI at both the 5th and 95th percentile increased; 90% of the BMIs in a population lie between these percentiles so these BMI values indicate the spread of the BMI distribution. However, the BMI at the 95th percentile increased about 2.5 times faster than the BMI at the 5th percentile. Moreover, with increasing average BMI, the prevalence of overweight and obesity increased faster than the decline in the prevalence of underweight. Finally, quantile-quantile plots for each country (a graphical method that compares two distributions) revealed a consistent pattern of unequal weight gain across the BMI distribution as average BMI increased, with pronounced weight gains at the obese end of the distribution and little change at the underweight end.
What Do These Findings Mean?
These findings show that increases in average BMI are associated with an increased spread of BMI across and within populations. Consequently, changes in average BMI or single measurements such as the prevalence of overweight do not capture the divergence in the degree of weight gain occurring between that part of the population that has a low BMI and that part that has a high BMI. In other words, at least for the low- and middle-income countries included in this study, population weight gain is occurring disproportionately among groups with high baseline BMI levels. The researchers suggest, therefore, that the characterization of the BMI of populations over time should examine the patterns of change across the whole BMI distribution. Moreover, rather than a single broad population strategy for weight control, optimum health outcomes, they suggest, might be achieved by a strategy that includes targeted interventions to reduce weight in high BMI segments of the population and to increase weight in low BMI segments.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001367.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish)
The World Health Organization provides information on obesity (in several languages); Malri's story describes the health risks faced by an obese child
The UK National Health Service Choices website also provides detailed information about obesity and a link to a personal story about losing weight
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
MedlinePlus has links to further information about obesity (in English and Spanish)
doi:10.1371/journal.pmed.1001367
PMCID: PMC3545870  PMID: 23335861
7.  Association analysis of the SLC22A11 (organic anion transporter 4) and SLC22A12 (urate transporter 1) urate transporter locus with gout in New Zealand case-control sample sets reveals multiple ancestral-specific effects 
Arthritis Research & Therapy  2013;15(6):R220.
Introduction
There is inconsistent association between urate transporters SLC22A11 (organic anion transporter 4 (OAT4)) and SLC22A12 (urate transporter 1 (URAT1)) and risk of gout. New Zealand (NZ) Māori and Pacific Island people have higher serum urate and more severe gout than European people. The aim of this study was to test genetic variation across the SLC22A11/SLC22A12 locus for association with risk of gout in NZ sample sets.
Methods
A total of 12 single nucleotide polymorphism (SNP) variants in four haplotype blocks were genotyped using TaqMan® and Sequenom MassArray in 1003 gout cases and 1156 controls. All cases had gout according to the 1977 American Rheumatism Association criteria. Association analysis of single markers and haplotypes was performed using PLINK and Stata.
Results
A haplotype block 1 SNP (rs17299124) (upstream of SLC22A11) was associated with gout in less admixed Polynesian sample sets, but not European Caucasian (odds ratio; OR = 3.38, P = 6.1 × 10-4; OR = 0.91, P = 0.40, respectively) sample sets. A protective block 1 haplotype caused the rs17299124 association (OR = 0.28, P = 6.0 × 10-4). Within haplotype block 2 (SLC22A11) we could not replicate previous reports of association of rs2078267 with gout in European Caucasian (OR = 0.98, P = 0.82) sample sets, however this SNP was associated with gout in Polynesian (OR = 1.51, P = 0.022) sample sets. Within haplotype block 3 (including SLC22A12) analysis of haplotypes revealed a haplotype with trans-ancestral protective effects (OR = 0.80, P = 0.004), and a second haplotype conferring protection in less admixed Polynesian sample sets (OR = 0.63, P = 0.028) but risk in European Caucasian samples (OR = 1.33, P = 0.039).
Conclusions
Our analysis provides evidence for multiple ancestral-specific effects across the SLC22A11/SLC22A12 locus that presumably influence the activity of OAT4 and URAT1 and risk of gout. Further fine mapping of the association signal is needed using trans-ancestral re-sequence data.
doi:10.1186/ar4417
PMCID: PMC3978909  PMID: 24360580
8.  Genome-Wide Association Study of Serum Selenium Concentrations 
Nutrients  2013;5(5):1706-1718.
Selenium is an essential trace element and circulating selenium concentrations have been associated with a wide range of diseases. Candidate gene studies suggest that circulating selenium concentrations may be impacted by genetic variation; however, no study has comprehensively investigated this hypothesis. Therefore, we conducted a two-stage genome-wide association study to identify genetic variants associated with serum selenium concentrations in 1203 European descents from two cohorts: the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening and the Women’s Health Initiative (WHI). We tested association between 2,474,333 single nucleotide polymorphisms (SNPs) and serum selenium concentrations using linear regression models. In the first stage (PLCO) 41 SNPs clustered in 15 regions had p < 1 × 10−5. None of these 41 SNPs reached the significant threshold (p = 0.05/15 regions = 0.003) in the second stage (WHI). Three SNPs had p < 0.05 in the second stage (rs1395479 and rs1506807 in 4q34.3/AGA-NEIL3; and rs891684 in 17q24.3/SLC39A11) and had p between 2.62 × 10−7 and 4.04 × 10−7 in the combined analysis (PLCO + WHI). Additional studies are needed to replicate these findings. Identification of genetic variation that impacts selenium concentrations may contribute to a better understanding of which genes regulate circulating selenium concentrations.
doi:10.3390/nu5051706
PMCID: PMC3708345  PMID: 23698163
selenium; serum; selenoprotein; genome-wide association study; AGA; NEIL3; SLC39A11
9.  The genetic susceptibility to type 2 diabetes may be modulated by obesity status: implications for association studies 
BMC Medical Genetics  2008;9:45.
Background
Considering that a portion of the heterogeneity amongst previous replication studies may be due to a variable proportion of obese subjects in case-control designs, we assessed the association of genetic variants with type 2 diabetes (T2D) in large groups of obese and non-obese subjects.
Methods
We genotyped RETN, KCNJ11, HNF4A, HNF1A, GCK, SLC30A8, ENPP1, ADIPOQ, PPARG, and TCF7L2 polymorphisms in 1,283 normoglycemic (NG) and 1,581 T2D obese individuals as well as in 3,189 NG and 1,244 T2D non-obese subjects of European descent, allowing us to examine T2D risk over a wide range of BMI.
Results
Amongst non-obese individuals, we observed significant T2D associations with HNF1A I27L [odds ratio (OR) = 1.14, P = 0.04], GCK -30G>A (OR = 1.23, P = 0.01), SLC30A8 R325W (OR = 0.87, P = 0.04), and TCF7L2 rs7903146 (OR = 1.89, P = 4.5 × 10-23), and non-significant associations with PPARG Pro12Ala (OR = 0.85, P = 0.14), ADIPOQ -11,377C>G (OR = 1.00, P = 0.97) and ENPP1 K121Q (OR = 0.99, P = 0.94). In obese subjects, associations with T2D were detected with PPARG Pro12Ala (OR = 0.73, P = 0.004), ADIPOQ -11,377C>G (OR = 1.26, P = 0.02), ENPP1 K121Q (OR = 1.30, P = 0.003) and TCF7L2 rs7903146 (OR = 1.30, P = 1.1 × 10-4), and non-significant associations with HNF1A I27L (OR = 0.96, P = 0.53), GCK -30G>A (OR = 1.15, P = 0.12) and SLC30A8 R325W (OR = 0.95, P = 0.44). However, a genotypic heterogeneity was only found for TCF7L2 rs7903146 (P = 3.2 × 10-5) and ENPP1 K121Q (P = 0.02). No association with T2D was found for KCNJ11, RETN, and HNF4A polymorphisms in non-obese or in obese individuals.
Conclusion
Genetic variants modulating insulin action may have an increased effect on T2D susceptibility in the presence of obesity, whereas genetic variants acting on insulin secretion may have a greater impact on T2D susceptibility in non-obese individuals.
doi:10.1186/1471-2350-9-45
PMCID: PMC2412856  PMID: 18498634
10.  Allellic variants in regulatory regions of cyclooxygenase-2: association with advanced colorectal adenoma 
British journal of cancer  2005;93(8):953-959.
Cyclooxygenase 2 (Cox-2) is upregulated in colorectal adenomas and carcinomas. Polymorphisms in the Cox-2 gene may influence its function and/or its expression and may modify the protective effect of nonsteroidal anti-inflammatory drugs (NSAIDs), thereby impacting individuals’ risk of developing colorectal cancer and response to prevention/intervention strategies. In a nested case–control study, four polymorphisms in the Cox-2 gene (two in the promoter, −663 insertion/deletion, GT/(GT) and −798 A/G; one in intron 5-5229, T/G; one in 3′ untranslated region (UTR)-8494, T/C) were genotyped in 726 cases of colorectal adenomas and 729 age- and gender-matched controls in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial. There was no significant association between the Cox-2 polymorphisms and adenoma development in the overall population. However, in males, the relatively rare heterozygous genotype GT/(GT) at −663 in the promoter and the variant homozygous genotype G/G at intron 5-5229 appeared to have inverse associations (odds ratio (OR) = 0.59, confidence interval (CI): 0.34–1.02 and OR = 0.48, CI: 0.24–0.99, respectively), whereas the heterozygous genotype T/C at 3′UTR-8494 had a positive association (OR = 1.31, CI: 1.01–1.71) with adenoma development. Furthermore, the haplotype carrying the risk-conferring 3′UTR-8494 variant was associated with a 35% increase in the odds for adenoma incidence in males (OR = 1.35, CI: 1.07–1.70), but the one with a risk allele at 3′UTR-8494 and a protective allele at intron 5-5229 had no effect on adenoma development (OR = 0.85, CI: 0.66–1.09). Gender-related differences in adenoma risk were also noted with tobacco usage and protective effects of NSAIDs. Our analysis underscores the significance of the overall allelic architecture of Cox-2 as an important determinant for risk assessment.
doi:10.1038/sj.bjc.6602806
PMCID: PMC1369968  PMID: 16205694
cyclooxygenase-2; colorectal adenomas; polymorphisms; haplotypes
11.  Allellic variants in regulatory regions of cyclooxygenase-2: association with advanced colorectal adenoma 
British Journal of Cancer  2005;93(8):953-959.
Cyclooxygenase 2 (Cox-2) is upregulated in colorectal adenomas and carcinomas. Polymorphisms in the Cox-2 gene may influence its function and/or its expression and may modify the protective effect of nonsteroidal anti-inflammatory drugs (NSAIDs), thereby impacting individuals' risk of developing colorectal cancer and response to prevention/intervention strategies. In a nested case–control study, four polymorphisms in the Cox-2 gene (two in the promoter, −663 insertion/deletion, GT/(GT) and −798 A/G; one in intron 5-5229, T/G; one in 3′untranslated region (UTR)-8494, T/C) were genotyped in 726 cases of colorectal adenomas and 729 age- and gender-matched controls in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial. There was no significant association between the Cox-2 polymorphisms and adenoma development in the overall population. However, in males, the relatively rare heterozygous genotype GT/(GT) at −663 in the promoter and the variant homozygous genotype G/G at intron 5-5229 appeared to have inverse associations (odds ratio (OR)=0.59, confidence interval (CI): 0.34–1.02 and OR=0.48, CI: 0.24–0.99, respectively), whereas the heterozygous genotype T/C at 3′UTR-8494 had a positive association (OR=1.31, CI: 1.01–1.71) with adenoma development. Furthermore, the haplotype carrying the risk-conferring 3′UTR-8494 variant was associated with a 35% increase in the odds for adenoma incidence in males (OR=1.35, CI: 1.07–1.70), but the one with a risk allele at 3′UTR-8494 and a protective allele at intron 5-5229 had no effect on adenoma development (OR=0.85, CI: 0.66–1.09). Gender-related differences in adenoma risk were also noted with tobacco usage and protective effects of NSAIDs. Our analysis underscores the significance of the overall allelic architecture of Cox-2 as an important determinant for risk assessment.
doi:10.1038/sj.bjc.6602806
PMCID: PMC1369968  PMID: 16205694
cyclooxygenase-2; colorectal adenomas; polymorphisms; haplotypes
12.  Body Mass Index and Colon Cancer Screening: A Systematic Review and Meta-Analysis 
Background
Obesity is associated with increased colon cancer mortality and lower rates of mammography and Pap testing.
Methods
We conducted a systematic review to determine if obesity is associated with lower rates of colon cancer screening. We searched the PubMed, CINAHL, and Cochrane Library databases. Two investigators reviewed citations, abstracts, and articles independently. Two investigators abstracted study information sequentially and evaluated quality independently using standardized forms. We included all studies in our qualitative syntheses. We used random effects meta-analyses to combine those studies providing screening results by the following BMI categories: Normal, 18.5–24.9 kg/m2 (reference); overweight, 25–29.9 kg/m2; class I obesity, 30–34.9 kg/m2; class II obesity, 35–39.9 kg/m2; and class III obesity, ≥ 40 kg/ m2.
Results
Of 5,543 citations, we included 23 articles. Almost all studies were cross-sectional and ascertained BMI and screening through self report. BMI was not associated with colon cancer screening overall. The subgroup of obese white women reported lower rates of colon cancer screening compared to those with a normal BMI with combined odds ratios (95% CI) of 0.87 (0.82 to 0.93), 0.80 (0.65 to 0.99), and 0.73 (0.54 to 0.94) for class I, II, and III obesity, respectively. Results were similar among white men with class II obesity.
Conclusions
Overall, BMI was not associated with colon cancer screening. Obese white men and women may be less likely to undergo colon cancer screening compared to those with a normal BMI.
Impact
Further investigation of this disparity may reduce the risk of obesity-related colon cancer death.
doi:10.1158/1055-9965.EPI-11-0826
PMCID: PMC3930882  PMID: 22492832
Colon cancer screening; obesity; meta-analysis; screening; prevention; disparity
13.  SLC2A9 Is a High-Capacity Urate Transporter in Humans 
PLoS Medicine  2008;5(10):e197.
Background
Serum uric acid levels in humans are influenced by diet, cellular breakdown, and renal elimination, and correlate with blood pressure, metabolic syndrome, diabetes, gout, and cardiovascular disease. Recent genome-wide association scans have found common genetic variants of SLC2A9 to be associated with increased serum urate level and gout. The SLC2A9 gene encodes a facilitative glucose transporter, and it has two splice variants that are highly expressed in the proximal nephron, a key site for urate handling in the kidney. We investigated whether SLC2A9 is a functional urate transporter that contributes to the longstanding association between urate and blood pressure in man.
Methods and Findings
We expressed both SLC2A9 splice variants in Xenopus laevis oocytes and found both isoforms mediate rapid urate fluxes at concentration ranges similar to physiological serum levels (200–500 μM). Because SLC2A9 is a known facilitative glucose transporter, we also tested whether glucose or fructose influenced urate transport. We found that urate is transported by SLC2A9 at rates 45- to 60-fold faster than glucose, and demonstrated that SLC2A9-mediated urate transport is facilitated by glucose and, to a lesser extent, fructose. In addition, transport is inhibited by the uricosuric benzbromarone in a dose-dependent manner (Ki = 27 μM). Furthermore, we found urate uptake was at least 2-fold greater in human embryonic kidney (HEK) cells overexpressing SLC2A9 splice variants than nontransfected kidney cells. To confirm that our findings were due to SLC2A9, and not another urate transporter, we showed that urate transport was diminished by SLC2A9-targeted siRNA in a second mammalian cell line. In a cohort of men we showed that genetic variants of SLC2A9 are associated with reduced urinary urate clearance, which fits with common variation at SLC2A9 leading to increased serum urate. We found no evidence of association with hypertension (odds ratio 0.98, 95% confidence interval [CI] 0.9 to 1.05, p > 0.33) by meta-analysis of an SLC2A9 variant in six case–control studies including 11,897 participants. In a separate meta-analysis of four population studies including 11,629 participants we found no association of SLC2A9 with systolic (effect size −0.12 mm Hg, 95% CI −0.68 to 0.43, p = 0.664) or diastolic blood pressure (effect size −0.03 mm Hg, 95% CI −0.39 to 0.31, p = 0.82).
Conclusions
This study provides evidence that SLC2A9 splice variants act as high-capacity urate transporters and is one of the first functional characterisations of findings from genome-wide association scans. We did not find an association of the SLC2A9 gene with blood pressure in this study. Our findings suggest potential pathogenic mechanisms that could offer a new drug target for gout.
Editors' Summary
Background.
Blood is continually pumped around the human body to deliver the chemicals needed to keep the body's cells alive and to take cellular waste products to the kidneys where they are filtered out of the blood and excreted in the urine. In healthy people, the levels of nutrients and waste products in serum (the liquid part of blood) fall within “normal” ranges but in ill people these levels can be very different. For example, serum uric acid (urate) levels are usually increased in people with gout. In this arthritic condition, uric acid crystallizes in the joints (often those in the big toe) and causes swelling and intense pain. Increased serum urate levels, which are also associated with high blood pressure, diabetes, and several other important conditions, can be caused by eating food that is rich in chemicals called purines (for example, liver, dried beans, and port). The body also converts its own purines into uric acid so genetic variations in the enzymes involved in purine breakdown can alter serum urate levels, as can variations in the rate of urate removal from the body by the kidneys. Urinary urate excretion is controlled by urate transporters, proteins that carry urate into and out of the kidney cells. Uricosuric drugs, which are used to treat gout, reduce serum urate levels by inhibiting a urate transporter that reabsorbs urate from urine.
Why Was This Study Done?
Several urate transporters have already been identified but recently, using an approach called genome-wide association scanning, scientists found that some genetic variants of a human gene called SLC2A9 are more common in people with high serum urate levels than in people with normal levels. SLC2A9 encodes a glucose transporter (a protein that helps to move the sugar glucose through cell membranes) and is highly expressed in the kidney's main urate handling site. Given these facts, could SLC2A9 (the protein made from SLC2A9) be a urate transporter as well as a glucose transporter? In this study, the researchers investigate this possibility and also ask whether genetic variations in SLC2A9 might be responsible for the association between serum urate levels and high blood pressure.
What Did the Researchers Do and Find?
The researchers first expressed SLC2A9 in frog eggs, a type of cell that does not have its own urate transporter. They found that urate rapidly moved into eggs expressing SLC2A9 but not into control eggs, that SLC2A9 transported urate about 50 times faster than glucose, and that glucose stimulated SLC2A9-mediated urate transport. Similarly, overexpression of SLC2A9 in human embryonic kidney cells more than doubled their urate uptake. Conversely, when the researchers used a technique called RNA interference to reduce the expression of mouse SLC2A9 in mouse cells that normally makes this protein, urate transport was reduced. Next, the researchers looked at two small parts of SLC2A9 that vary between individuals (so-called single polynucleotide polymorphisms) in nearly 900 men who had had their serum urate levels and urinary urate excretion rates measured. They found that certain genetic variations at these two sites were associated with increased serum urate levels and decreased urinary urate excretion. Finally, the researchers used a statistical technique called meta-analysis to look for an association between one of the SLC2A9 gene variants and blood pressure. In two separate meta-analyses that together involved more than 20, 000 participants in several studies, there was no association between this gene variant and blood pressure.
What Do These Findings Mean?
Overall, these findings indicate that SLCA9 is a high capacity urate transporter and suggest that this protein plays an important part in controlling serum urate levels. They provide confirmation that common genetic variants in SLC2A9 affect serum urate levels to a marked degree, although they do not show exactly which genetic variant is responsible for increasing serum urate levels. They also provide important new insights into how the kidneys normally handle urate and suggest ways in which this essential process may sometimes go wrong. Thus, these findings could eventually lead to new treatments for gout and possibly for other diseases that are associated with increased serum urate levels.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050197.
The UK National Health Service Direct health encyclopedia provides detailed information for patients about gout
MedlinePlus provides links to many sources of information about gout (in English and Spanish), including “What is gout?”, an easy-to-read guide from the US National Institutes of Arthritis and Musculoskeletal and Skin Diseases
Wikipedia also has pages on gout, uric acid, and SCL2A9 (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
The Arthritis Research Campaign also has information on gout
Mark Caulfield and colleagues show that theSLC2A9 gene, which encodes a facilitative glucose transporter, is also a high-capacity urate transporter.
doi:10.1371/journal.pmed.0050197
PMCID: PMC2561076  PMID: 18842065
14.  Risk Prediction for Breast, Endometrial, and Ovarian Cancer in White Women Aged 50 y or Older: Derivation and Validation from Population-Based Cohort Studies 
PLoS Medicine  2013;10(7):e1001492.
Ruth Pfeiffer and colleagues describe models to calculate absolute risks for breast, endometrial, and ovarian cancers for white, non-Hispanic women over 50 years old using easily obtainable risk factors.
Please see later in the article for the Editors' Summary
Background
Breast, endometrial, and ovarian cancers share some hormonal and epidemiologic risk factors. While several models predict absolute risk of breast cancer, there are few models for ovarian cancer in the general population, and none for endometrial cancer.
Methods and Findings
Using data on white, non-Hispanic women aged 50+ y from two large population-based cohorts (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial [PLCO] and the National Institutes of Health–AARP Diet and Health Study [NIH-AARP]), we estimated relative and attributable risks and combined them with age-specific US-population incidence and competing mortality rates. All models included parity. The breast cancer model additionally included estrogen and progestin menopausal hormone therapy (MHT) use, other MHT use, age at first live birth, menopausal status, age at menopause, family history of breast or ovarian cancer, benign breast disease/biopsies, alcohol consumption, and body mass index (BMI); the endometrial model included menopausal status, age at menopause, BMI, smoking, oral contraceptive use, MHT use, and an interaction term between BMI and MHT use; the ovarian model included oral contraceptive use, MHT use, and family history or breast or ovarian cancer. In independent validation data (Nurses' Health Study cohort) the breast and ovarian cancer models were well calibrated; expected to observed cancer ratios were 1.00 (95% confidence interval [CI]: 0.96–1.04) for breast cancer and 1.08 (95% CI: 0.97–1.19) for ovarian cancer. The number of endometrial cancers was significantly overestimated, expected/observed = 1.20 (95% CI: 1.11–1.29). The areas under the receiver operating characteristic curves (AUCs; discriminatory power) were 0.58 (95% CI: 0.57–0.59), 0.59 (95% CI: 0.56–0.63), and 0.68 (95% CI: 0.66–0.70) for the breast, ovarian, and endometrial models, respectively.
Conclusions
These models predict absolute risks for breast, endometrial, and ovarian cancers from easily obtainable risk factors and may assist in clinical decision-making. Limitations are the modest discriminatory ability of the breast and ovarian models and that these models may not generalize to women of other races.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In 2008, just three types of cancer accounted for 10% of global cancer-related deaths. That year, about 460,000 women died from breast cancer (the most frequently diagnosed cancer among women and the fifth most common cause of cancer-related death). Another 140,000 women died from ovarian cancer, and 74,000 died from endometrial (womb) cancer (the 14th and 20th most common causes of cancer-related death, respectively). Although these three cancers originate in different tissues, they nevertheless share many risk factors. For example, current age, age at menarche (first period), and parity (the number of children a woman has had) are all strongly associated with breast, ovarian, and endometrial cancer risk. Because these cancers share many hormonal and epidemiological risk factors, a woman with a high breast cancer risk is also likely to have an above-average risk of developing ovarian or endometrial cancer.
Why Was This Study Done?
Several statistical models (for example, the Breast Cancer Risk Assessment Tool) have been developed that estimate a woman's absolute risk (probability) of developing breast cancer over the next few years or over her lifetime. Absolute risk prediction models are useful in the design of cancer prevention trials and can also help women make informed decisions about cancer prevention and treatment options. For example, a woman at high risk of breast cancer might decide to take tamoxifen for breast cancer prevention, but ideally she needs to know her absolute endometrial cancer risk before doing so because tamoxifen increases the risk of this cancer. Similarly, knowledge of her ovarian cancer risk might influence a woman's decision regarding prophylactic removal of her ovaries to reduce her breast cancer risk. There are few absolute risk prediction models for ovarian cancer, and none for endometrial cancer, so here the researchers develop models to predict the risk of these cancers and of breast cancer.
What Did the Researchers Do and Find?
Absolute risk prediction models are constructed by combining estimates for risk factors from cohorts with population-based incidence rates from cancer registries. Models are validated in an independent cohort by testing their ability to identify people with the disease in an independent cohort and their ability to predict the observed numbers of incident cases. The researchers used data on white, non-Hispanic women aged 50 years or older that were collected during two large prospective US cohort studies of cancer screening and of diet and health, and US cancer incidence and mortality rates provided by the Surveillance, Epidemiology, and End Results Program to build their models. The models all included parity as a risk factor, as well as other factors. The model for endometrial cancer, for example, also included menopausal status, age at menopause, body mass index (an indicator of the amount of body fat), oral contraceptive use, menopausal hormone therapy use, and an interaction term between menopausal hormone therapy use and body mass index. Individual women's risk for endometrial cancer calculated using this model ranged from 1.22% to 17.8% over the next 20 years depending on their exposure to various risk factors. Validation of the models using data from the US Nurses' Health Study indicated that the endometrial cancer model overestimated the risk of endometrial cancer but that the breast and ovarian cancer models were well calibrated—the predicted and observed risks for these cancers in the validation cohort agreed closely. Finally, the discriminatory power of the models (a measure of how well a model separates people who have a disease from people who do not have the disease) was modest for the breast and ovarian cancer models but somewhat better for the endometrial cancer model.
What Do These Findings Mean?
These findings show that breast, ovarian, and endometrial cancer can all be predicted using information on known risk factors for these cancers that is easily obtainable. Because these models were constructed and validated using data from white, non-Hispanic women aged 50 years or older, they may not accurately predict absolute risk for these cancers for women of other races or ethnicities. Moreover, the modest discriminatory power of the breast and ovarian cancer models means they cannot be used to decide which women should be routinely screened for these cancers. Importantly, however, these well-calibrated models should provide realistic information about an individual's risk of developing breast, ovarian, or endometrial cancer that can be used in clinical decision-making and that may assist in the identification of potential participants for research studies.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001492.
This study is further discussed in a PLOS Medicine Perspective by Lars Holmberg and Andrew Vickers
The US National Cancer Institute provides comprehensive information about cancer (in English and Spanish), including detailed information about breast cancer, ovarian cancer, and endometrial cancer;
Information on the Breast Cancer Risk Assessment Tool, the Surveillance, Epidemiology, and End Results Program, and on the prospective cohort study of screening and the diet and health study that provided the data used to build the models is also available on the NCI site
Cancer Research UK, a not-for-profit organization, provides information about cancer, including detailed information on breast cancer, ovarian cancer, and endometrial cancer
The UK National Health Service Choices website has information and personal stories about breast cancer, ovarian cancer, and endometrial cancer; the not-for-profit organization Healthtalkonline also provides personal stories about dealing with breast cancer and ovarian cancer
doi:10.1371/journal.pmed.1001492
PMCID: PMC3728034  PMID: 23935463
15.  Genetic Markers of Adult Obesity Risk Are Associated with Greater Early Infancy Weight Gain and Growth 
PLoS Medicine  2010;7(5):e1000284.
Ken Ong and colleagues genotyped children from the ALSPAC birth cohort and showed an association between greater early infancy gains in weight and length and genetic markers for adult obesity risk.
Background
Genome-wide studies have identified several common genetic variants that are robustly associated with adult obesity risk. Exploration of these genotype associations in children may provide insights into the timing of weight changes leading to adult obesity.
Methods and Findings
Children from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort were genotyped for ten genetic variants previously associated with adult BMI. Eight variants that showed individual associations with childhood BMI (in/near: FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, and ETV5) were used to derive an “obesity-risk-allele score” comprising the total number of risk alleles (range: 2–15 alleles) in each child with complete genotype data (n = 7,146). Repeated measurements of weight, length/height, and body mass index from birth to age 11 years were expressed as standard deviation scores (SDS). Early infancy was defined as birth to age 6 weeks, and early infancy failure to thrive was defined as weight gain between below the 5th centile, adjusted for birth weight. The obesity-risk-allele score showed little association with birth weight (regression coefficient: 0.01 SDS per allele; 95% CI 0.00–0.02), but had an apparently much larger positive effect on early infancy weight gain (0.119 SDS/allele/year; 0.023–0.216) than on subsequent childhood weight gain (0.004 SDS/allele/year; 0.004–0.005). The obesity-risk-allele score was also positively associated with early infancy length gain (0.158 SDS/allele/year; 0.032–0.284) and with reduced risk of early infancy failure to thrive (odds ratio  = 0.92 per allele; 0.86–0.98; p = 0.009).
Conclusions
The use of robust genetic markers identified greater early infancy gains in weight and length as being on the pathway to adult obesity risk in a contemporary birth cohort.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The proportion of overweight and obese children is increasing across the globe. In the US, the Surgeon General estimates that, compared with 1980, twice as many children and three times the number of adolescents are now overweight. Worldwide, 22 million children under five years old are considered by the World Health Organization to be overweight.
Being overweight or obese in childhood is associated with poor physical and mental health. In addition, childhood obesity is considered a major risk factor for adult obesity, which is itself a major risk factor for cancer, heart disease, diabetes, osteoarthritis, and other chronic conditions.
The most commonly used measure of whether an adult is a healthy weight is body mass index (BMI), defined as weight in kilograms/(height in metres)2. However, adult categories of obese (>30) and overweight (>25) BMI are not directly applicable to children, whose BMI naturally varies as they grow. BMI can be used to screen children for being overweight and or obese but a diagnosis requires further information.
Why Was This Study Done?
As the numbers of obese and overweight children increase, a corresponding rise in future numbers of overweight and obese adults is also expected. This in turn is expected to lead to an increasing incidence of poor health. As a result, there is great interest among health professionals in possible pathways between childhood and adult obesity. It has been proposed that certain periods in childhood may be critical for the development of obesity.
In the last few years, ten genetic variants have been found to be more common in overweight or obese adults. Eight of these have also been linked to childhood BMI and/or obesity. The authors wanted to identify the timing of childhood weight changes that may be associated with adult obesity. Knowledge of obesity risk genetic variants gave them an opportunity to do so now, without following a set of children to adulthood.
What Did the Researchers Do and Find?
The authors analysed data gathered from a subset of 7,146 singleton white European children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, which is investigating associations between genetics, lifestyle, and health outcomes for a group of children in Bristol whose due date of birth fell between April 1991 and December 1992. They used knowledge of the children's genetic makeup to find associations between an obesity risk allele score—a measure of how many of the obesity risk genetic variants a child possessed—and the children's weight, height, BMI, levels of body fat (at nine years old), and rate of weight gain, up to age 11 years.
They found that, at birth, children with a higher obesity risk allele score were not any heavier, but in the immediate postnatal period they were less likely to be in the bottom 5% of the population for weight gain (adjusted for birthweight), often termed “failure to thrive.” At six weeks of age, children with a higher obesity risk allele score tended to be longer and heavier, even allowing for weight at birth.
After six weeks of age, the obesity risk allele score was not associated with any further increase in length/height, but it was associated with a more rapid weight gain between birth and age 11 years. BMI is derived from height and weight measurements, and the association between the obesity risk allele score and BMI was weak between birth and age three-and-a-half years, but after that age the association with BMI increased rapidly. By age nine, children with a higher obesity risk allele score tended to be heavier and taller, with more fat on their bodies.
What Do These Findings Mean?
The combined obesity allele risk score is associated with higher rates of weight gain and adult obesity, and so the authors conclude that weight gain and growth even in the first few weeks after birth may be the beginning of a pathway of greater adult obesity risk.
A study that tracks a population over time can find associations but it cannot show cause and effect. In addition, only a relatively small proportion (1.7%) of the variation in BMI at nine years of age is explained by the obesity risk allele score.
The authors' method of finding associations between childhood events and adult outcomes via genetic markers of risk of disease as an adult has a significant advantage: the authors did not have to follow the children themselves to adulthood, so their findings are more likely to be relevant to current populations. Despite this, this research does not yield advice for parents how to reduce their children's obesity risk. It does suggest that “failure to thrive” in the first six weeks of life is not simply due to a lack of provision of food by the baby's caregiver but that genetic factors also contribute to early weight gain and growth.
The study looked at the combined obesity risk allele score and the authors did not attempt to identify which individual alleles have greater or weaker associations with weight gain and overweight or obesity. This would require further research based on far larger numbers of babies and children. The findings may also not be relevant to children in other types of setting because of the effects of different nutrition and lifestyles.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000284.
Further information is available on the ALSPAC study
The UK National Health Service and other partners provide guidance on establishing a healthy lifestyle for children and families in their Change4Life programme
The International Obesity Taskforce is a global network of expertise and the advocacy arm of the International Association for the Study of Obesity. It works with the World Health Organization, other NGOs, and stakeholders and provides information on overweight and obesity
The Centers for Disease Control and Prevention (CDC) in the US provide guidance and tips on maintaining a healthy weight, including BMI calculators in both metric and Imperial measurements for both adults and children. They also provide BMI growth charts for boys and girls showing how healthy ranges vary for each sex at with age
The Royal College of Paediatrics and Child Health provides growth charts for weight and length/height from birth to age 4 years that are based on WHO 2006 growth standards and have been adapted for use in the UK
The CDC Web site provides information on overweight and obesity in adults and children, including definitions, causes, and data
The CDC also provide information on the role of genes in causing obesity.
The World Health Organization publishes a fact sheet on obesity, overweight and weight management, including links to childhood overweight and obesity
Wikipedia includes an article on childhood obesity (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1000284
PMCID: PMC2876048  PMID: 20520848
16.  Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts 
PLoS Medicine  2013;10(2):e1001383.
A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity.
Background
Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis.
Methods and Findings
We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects.
Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores).
Conclusions
On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements.
Why Was This Study Done?
Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations.
What Did the Researchers Do and Find?
The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium.
What Do These Findings Mean?
These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population
The World Health Organization provides information on obesity (in several languages)
The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish)
MedlinePlus has links to further information about obesity and about vitamin D (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)
Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits
doi:10.1371/journal.pmed.1001383
PMCID: PMC3564800  PMID: 23393431
17.  The SLC6A14 gene shows evidence of association with obesity 
Journal of Clinical Investigation  2003;112(11):1762-1772.
In our previous genome-wide scan of Finnish nuclear families, obesity was linked to chromosome Xq24. Here we analyzed this 15-Mb region by genotyping 9 microsatellite markers and 36 single nucleotide polymorphisms (SNPs) for 11 positional and functional candidate genes in an extended sample of 218 obese Finnish sibling pairs (sibpairs) (BMI > 30 kg/m2). Evidence of linkage emerged mainly from the obese male sibpairs, suggesting a gender-specific effect for the underlying gene. By constructing haplotypes among the obese male sibpairs, we restricted the region from 15 Mb to 4 Mb, between markers DXS8088 and DXS8067. Regional functional candidate genes were tested for association in an initial sample of 117 cases and 182 controls. Significant evidence was observed for association for an SNP in the 3′-untranslated region of the solute carrier family 6 member 14 (SLC6A14) gene (P = 0.0002) and for SNP haplotypes of the SLC6A14 gene (P = 0.0007–0.006). Furthermore, an independent replication study sample of 837 cases and 968 controls from Finland and Sweden also showed significant differences in allele frequencies between obese and non-obese individuals (P = 0.003). The SLC6A14 gene is an interesting novel candidate for obesity because it encodes an amino acid transporter, which potentially regulates tryptophan availability for serotonin synthesis and thus possibly affects appetite control.
doi:10.1172/JCI200317491
PMCID: PMC281637  PMID: 14660752
18.  The Association Between the SLC6A3 VNTR 9-Repeat Allele and Alcoholism—A Meta-Analysis 
Background
Dopamine transporter gene (SLC6A3) represents a promising candidate involved in the development of alcoholism. This study aimed to explore the association between the 9-repeat allele (A9) of a 40-bp variable number tandem repeat (VNTR) polymorphism in the 3′ untranslated region (3′ UTR) of the SLC6A3 gene and alcoholism.
Methods
The SLC6A3 VNTR was genotyped by PCR in unrelated Mexican Americans including 337 controls and 365 alcoholics. Pearson's chi-square test or Fisher's exact test was used to compare the genotype and allele distribution. Meta-analyses were performed for population-based case–control association studies of the SLC6A3 VNTR polymorphism with alcoholism. Data were analyzed under random effect models with the Comprehensive Meta-analysis (v.2) statistical software package.
Results
In Mexican Americans, no significant difference was found in allele and genotype distribution between controls and alcoholics or between controls and alcoholics with alcohol withdrawal seizure (AWS) or delirium tremens (DT) (unadjusted p > 0.05). A total of 13 research articles were included in the meta-analyses. No significant difference of the SLC6A3 VNTR A9 was noted between controls and alcoholics at the genotypic and allelic level when all ethnic populations, only Caucasian populations, or only Asian populations were considered (p > 0.05). Significant associations were observed between SLC6A3 VNTR A9 and alcoholics with AWS or DT at the genotypic as well as allelic level when all ethnic populations or only Caucasian populations were considered (p < 0.05, OR 1.5–2.1).
Conclusions
Meta-analyses suggest a possible association between the SLC6A3 VNTR A9 and alcoholic subgroup with AWS or DT.
doi:10.1111/j.1530-0277.2011.01509.x
PMCID: PMC4084904  PMID: 21554332
Alcoholism; Dopamine Transporter; Variable Number Tandem Repeat; Meta-Analysis; Mexican American
19.  AVPR1a and SLC6A4 Gene Polymorphisms Are Associated with Creative Dance Performance 
PLoS Genetics  2005;1(3):e42.
Dancing, which is integrally related to music, likely has its origins close to the birth of Homo sapiens, and throughout our history, dancing has been universally practiced in all societies. We hypothesized that there are differences among individuals in aptitude, propensity, and need for dancing that may partially be based on differences in common genetic polymorphisms. Identifying such differences may lead to an understanding of the neurobiological basis of one of mankind's most universal and appealing behavioral traits—dancing. In the current study, 85 current performing dancers and their parents were genotyped for the serotonin transporter (SLC6A4: promoter region HTTLPR and intron 2 VNTR) and the arginine vasopressin receptor 1a (AVPR1a: promoter microsatellites RS1 and RS3). We also genotyped 91 competitive athletes and a group of nondancers/nonathletes (n = 872 subjects from 414 families). Dancers scored higher on the Tellegen Absorption Scale, a questionnaire that correlates positively with spirituality and altered states of consciousness, as well as the Reward Dependence factor in Cloninger's Tridimensional Personality Questionnaire, a measure of need for social contact and openness to communication. Highly significant differences in AVPR1a haplotype frequencies (RS1 and RS3), especially when conditional on both SLC6A4 polymorphisms (HTTLPR and VNTR), were observed between dancers and athletes using the UNPHASED program package (Cocaphase: likelihood ratio test [LRS] = 89.23, p = 0.000044). Similar results were obtained when dancers were compared to nondancers/nonathletes (Cocaphase: LRS = 92.76, p = 0.000024). These results were confirmed using a robust family-based test (Tdtphase: LRS = 46.64, p = 0.010). Association was also observed between Tellegen Absorption Scale scores and AVPR1a (Qtdtphase: global chi-square = 26.53, p = 0.047), SLC6A4 haplotypes (Qtdtphase: chi-square = 2.363, p = 0.018), and AVPR1a conditional on SCL6A4 (Tdtphase: LRS = 250.44, p = 0.011). Similarly, significant association was observed between Tridimensional Personality Questionnaire Reward Dependence scores and AVPR1a RS1 (chi-square = 20.16, p = 0.01). Two-locus analysis (RS1 and RS3 conditional on HTTLPR and VNTR) was highly significant (LRS = 162.95, p = 0.001). Promoter repeat regions in the AVPR1a gene have been robustly demonstrated to play a role in molding a range of social behaviors in many vertebrates and, more recently, in humans. Additionally, serotonergic neurotransmission in some human studies appears to mediate human religious and spiritual experiences. We therefore hypothesize that the association between AVPR1a and SLC6A4 reflects the social communication, courtship, and spiritual facets of the dancing phenotype rather than other aspects of this complex phenotype, such as sensorimotor integration.
Synopsis
Dancing, integrally related to music, likely has its origins close to the birth of Homo sapiens. The authors hypothesized that there are differences in aptitude, propensity, and need for dancing that may be based on differences in common genetic polymorphisms. Identifying such differences may lead to an understanding of the neurobiological basis of dancing.
Variants of the serotonin transporter and the arginine vasopressin receptor 1a genes were examined in performing dancers, elite athletes, and nonathletes/nondancers. The serotonin transporter regulates the level of serotonin, a brain transmitter that contributes to spiritual experience. The vasopressin receptor has been shown in many animal studies to modulate social communication and affiliative behaviors. Notably, dancers scored high on the Tellegen Absorption Scale, a correlate of spirituality, and the Reward Dependence factor in Cloninger's Tridimensional Personality Questionnaire, a measure of empathy, social communication, and need for social contact. Significant differences were observed in allele frequencies for both genes when dancers were compared to athletes as well as to nondancers/nonathletes. These two genes were also associated with scores on the Tellegen Absorption Scale and Tridimensional Personality Questionnaire Reward Dependence, suggesting that the association between these genes and dance is mediated by personality factors reflecting the social communication, courtship, and spiritual facets of the dancing phenotype.
doi:10.1371/journal.pgen.0010042
PMCID: PMC1239939  PMID: 16205790
20.  Association analyses for dopamine receptor gene polymorphisms and weight status in a longitudinal analysis in obese children before and after lifestyle intervention 
BMC Pediatrics  2013;13:197.
Background
Dopamine receptors are involved in midbrain reward circuit activation. Polymorphisms in two dopamine receptor genes, DRD2 and DRD4, have been associated with altered perception of food reward and weight gain. The objective of this study was to determine whether the same risk alleles were associated with overweight/obesity and with lower reduction of overweight after a 1-year lifestyle intervention.
Methods
In a longitudinal study the association of polymorphisms in DRD2 (rs18000497, risk allele: T, formerly A1 allele at the TaqI A1 polymorphism) and DRD4 (variable number of tandem repeats (VNTR); 48 bp repeat in exon III; risk alleles: 7 repeats or longer: 7R+) was tested on weight loss success following a 1-year lifestyle childhood obesity intervention (OBELDICKS). An additional exploratory cross-sectional case-control study was performed to compare the same DRD polymorphisms in these overweight/obese children and adolescents versus lean adult controls. Subjects were 423 obese and 28 overweight children participating in lifestyle intervention (203 males), age median 12.0 (interquartile range 10.0–13.7) years, body mass index - standard deviation score (BMI-SDS) 2.4 ± 0.5; 583 lean adults (232 males); age median 25.3 (interquartile range 22.5–26.8) years, BMI 19.1 ± 1.9 kg/m2. BMI, BMI-SDS and skinfold thickness measures were assessed at baseline and after 1 year; genotyping was performed for DRD2 risk variant rs1800497 and DRD4 exon III VNTR.
Results
The DRD2 genotype had a nominal effect on success in the weight loss intervention. The weakest BMI-SDS reduction was in children homozygous for two rs1800497 T-alleles (n = 11) compared to the combined group with zero (n = 308) or one (n = 132) rs1800497 T-allele (-0.08 ± 0.36 vs. -0.28 ± 0.34; p < 0.05). There was no association between the DRD4 VNTR alleles and genotypes and success in the weight loss intervention. No associations of the risk alleles of the DRD2 and DRD4 polymorphisms and obesity were observed in the cross-sectional part of the study.
Conclusions
We did not find association between polymorphisms in DRD2 and DRD4 genes and weight status. However, obese carriers of two DRD2 rs1800497 T-alleles may be at risk for weak responses to lifestyle interventions aimed at weight reduction.
Trial registration
Obesity intervention program “Obeldicks” is registered at clinicaltrials.gov (NCT00435734).
doi:10.1186/1471-2431-13-197
PMCID: PMC4219494  PMID: 24283216
Dopamine receptor polymorphisms; Obesity; Lifestyle intervention; Weight reduction
21.  Study of the serotonin transporter (SLC6A4) and BDNF genes in French patients with non syndromic mental deficiency 
BMC Medical Genetics  2010;11:30.
Background
Mental deficiency has been linked to abnormalities in cortical neuronal network connectivity and plasticity. These mechanisms are in part under the control of two interacting signalling pathways, the serotonergic and the brain-derived neurotrophic (BDNF) pathways. The aim of the current paper is to determine whether particular alleles or genotypes of two crucial genes of these systems, the serotonin transporter gene (SLC6A4) and the brain-derived neurotrophic factor gene (BDNF), are associated with mental deficiency (MD).
Methods
We analyzed four functional polymorphisms (rs25531, 5-HTTLPR, VNTR, rs3813034) of the SLC6A4 gene and one functional polymorphism (Val66 Met) of the BDNF gene in 98 patients with non-syndromic mental deficiency (NS-MD) and in an ethnically matched control population of 251 individuals.
Results
We found no significant differences in allele and genotype frequencies in the five polymorphisms studied in the SLC6A4 and BDNF genes of NS-MD patients versus control patients. While the comparison of the patterns of linkage disequilibrium (D') in the control and NS-MD populations revealed a degree of variability it did not, however, reach significance. No significant differences in frequencies of haplotypes and genotypes for VNTR/rs3813034 and rs25531/5-HTTLPR were observed.
Conclusion
Altogether, results from the present study do not support a role for any of the five functional polymorphisms of SLC6A4 and BDNF genes in the aetiology of NS-RM. Moreover, they suggest no epistatic interaction in NS-MD between polymorphisms in BDNF and SLC6A4. However, we suggest that further studies on these two pathways in NS-MD remain necessary.
doi:10.1186/1471-2350-11-30
PMCID: PMC2837021  PMID: 20175892
22.  Associations Between Anthropometry, Cigarette Smoking, Alcohol Consumption, and Non-Hodgkin Lymphoma in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 
American Journal of Epidemiology  2010;171(12):1270-1281.
Prospective studies of lifestyle and non-Hodgkin lymphoma (NHL) are conflicting, and some are inconsistent with case-control studies. The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial was used to evaluate risk of NHL and its subtypes in association with anthropometric factors, smoking, and alcohol consumption in a prospective cohort study. Lifestyle was assessed via questionnaire among 142,982 male and female participants aged 55–74 years enrolled in the PLCO Trial during 1993–2001. Hazard ratios and 95% confidence intervals were calculated using Cox proportional hazards regression. During 1,201,074 person-years of follow-up through 2006, 1,264 histologically confirmed NHL cases were identified. Higher body mass index (BMI; weight (kg)/height (m)2) at ages 20 and 50 years and at baseline was associated with increased NHL risk (Ptrend < 0.01 for all; e.g., for baseline BMI ≥30 vs. 18.5–24.9, hazard ratio = 1.32, 95% confidence interval: 1.13, 1.54). Smoking was not associated with NHL overall but was inversely associated with follicular lymphoma (ever smoking vs. never: hazard ratio = 0.62, 95% confidence interval: 0.45, 0.85). Alcohol consumption was unrelated to NHL (drinks/week: Ptrend = 0.187). These data support previous studies suggesting that BMI is positively associated with NHL, show an inverse association between smoking and follicular lymphoma (perhaps due to residual confounding), and do not support a causal association between alcohol and NHL.
doi:10.1093/aje/kwq085
PMCID: PMC2915494  PMID: 20494998
alcoholic beverages; anthropometry; body height; body mass index; body weight; life style; lymphoma; non-Hodgkin; smoking
23.  Sequence variations of ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1, CRHR1 and NTRK2: association with major depression and antidepressant response in Mexican-Americans 
Molecular Psychiatry  2009;14(12):1105-1118.
We studied seven genes that reflect events relevant to antidepressant action at four sequential levels: (1) entry into the brain, (2) binding to monoaminergic transporters, and (3) distal effects at the transcription level, resulting in (4) changes in neurotrophin and neuropeptide receptors. Those genes are ATP-binding cassette subfamily B member 1 (ABCB1), the noradrenaline, dopamine, and serotonin transporters (SLC6A2, SLC6A3 and SLC6A4), cyclic AMP-responsive element binding protein 1 (CREB1), corticotropin-releasing hormone receptor 1 (CRHR1) and neurotrophic tyrosine kinase type 2 receptor (NTRK2). Sequence variability for those genes was obtained in exonic and flanking regions. A total of 56 280 000 bp across were sequenced in 536 unrelated Mexican Americans from Los Angeles (264 controls and 272 major depressive disorder (MDD)). We detected in those individuals 419 single nucleotide polymorphisms (SNPs); the nucleotide diversity was 0.00054±0.0001. Of those, a total of 204 novel SNPs were identified, corresponding to 49% of all previously reported SNPs in those genes: 72 were in untranslated regions, 19 were in coding sequences of which 7 were non-synonymous, 86 were intronic and 27 were in upstream/downstream regions. Several SNPs or haplotypes in ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1 and NTRK2 were associated with MDD, and in ABCB1, SLC6A2 and NTRK2 with antidepressant response. After controlling for age, gender and baseline 21-item Hamilton Depression Rating Scale (HAM-D21) score, as well as correcting for multiple testing, the relative reduction of HAM-D21 score remained significantly associated with two NTRK2-coding SNPs (rs2289657 and rs56142442) and the haplotype CAG at rs2289658 (splice site), rs2289657 and rs2289656. Further studies in larger independent samples will be needed to confirm these associations. Our data indicate that extensive assessment of sequence variability may contribute to increase understanding of disease susceptibility and drug response. Moreover, these results highlight the importance of direct re-sequencing of key candidate genes in ethnic minority groups in order to discover novel genetic variants that cannot be simply inferred from existing databases.
doi:10.1038/mp.2009.92
PMCID: PMC2834349  PMID: 19844206
nucleotide polymorphism; antidepressant response; desipramine; fluoxetine; major depression
24.  Breast cancer epidemiology according to recognized breast cancer risk factors in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial Cohort 
BMC Cancer  2009;9:84.
Background
Multidisciplinary attempts to understand the etiology of breast cancer are expanding to increasingly include new potential markers of disease risk. Those efforts may have maximal scientific and practical influence if new findings are placed in context of the well-understood lifestyle and reproductive risk factors or existing risk prediction models for breast cancer. We therefore evaluated known risk factors for breast cancer in a cancer screening trial that does not have breast cancer as a study endpoint but is large enough to provide numerous analytic opportunities for breast cancer.
Methods
We evaluated risk factors for breast cancer (N = 2085) among 70,575 women who were randomized in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Using Poisson regression, we calculated adjusted relative risks [RRs, with 95% confidence intervals (CIs)] for lifestyle and reproductive factors during an average of 5 years of follow-up from date of randomization.
Results
As expected, increasing age, nulliparity, positive family history of breast cancer, and use of menopausal hormone therapy were positively associated with breast cancer. Later age at menarche (16 years or older vs. < 12: RR = 0.81, 95% CI, 0.65–1.02) or menopause (55 years or older vs. < 45: RR = 1.29, 95% CI, 1.03–1.62) were less strongly associated with breast cancer than was expected. There were weak positive associations between taller height and heavier weight, and only severe obesity [body mass index (BMI; kg/m2) 35 or more vs. 18.5–24.9: RR = 1.21, 95% CI, 1.02–1.43] was statistically significantly associated with breast cancer.
Conclusion
The ongoing PLCO trial offers continued opportunities for new breast cancer investigations, but these analyses suggest that the associations between breast cancer and age at menarche, age at menopause, and obesity might be changing as the underlying demographics of these factors change.
Clinical Trials Registration
http://www.clinicaltrials.gov, NCT00002540.
doi:10.1186/1471-2407-9-84
PMCID: PMC2670317  PMID: 19292893
25.  Effects of common haplotypes of the ileal sodium dependent bile acid transporter gene on the development of sporadic and familial colorectal cancer: A case control study 
BMC Medical Genetics  2008;9:70.
Background
The genetics of sporadic and non-syndromic familial colorectal cancer (CRC) is not well defined. However, genetic factors that promote the development of precursor lesions, i.e. adenomas, might also predispose to CRC. Recently, an association of colorectal adenoma with two variants (c.507C>T;p.L169L and c.511G>T;p.A171S) of the ileal sodium dependent bile acid transporter gene (SLC10A2) has been reported. Here, we reconstructed haplotypes of the SLC10A2 gene locus and tested for association with non-syndromic familial and sporadic CRC compared to 'hyper-normal' controls who displayed no colorectal polyps on screening colonoscopy.
Methods
We included 150 patients with sporadic CRC, 93 patients with familial CRC but exclusion of familial adenomatous polyposis and Lynch's syndrome, and 204 'hyper-normal' controls. Haplotype-tagging SLC10A2 gene variants were identified in the Hapmap database and genotyped using PCR-based 5' exonuclease assays with fluorescent dye-labelled probes. Haplotypes were reconstructed using the PHASE algorithm. Association testing was performed with both SNPs and reconstructed haplotypes.
Results
Minor allele frequencies of all SLC10A2 polymorphisms are within previously reported ranges, and no deviations from Hardy-Weinberg equilibrium are observed. However, we found no association with any of the SLC10A2 haplotypes with sporadic or familial CRC in our samples (all P values > 0.05).
Conclusion
Common variants of the SLC10A2 gene are not associated with sporadic or familial CRC. Hence, albeit this gene might be associated with early stages of colorectal neoplasia, it appears not to represent a major risk factor for progression to CRC.
doi:10.1186/1471-2350-9-70
PMCID: PMC2492852  PMID: 18644122

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