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1.  An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people 
Science (New York, N.Y.)  2012;337(6090):100-104.
Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (one every 17 bases) and geographically localized, such that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. Overall we conclude that, due to rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.
PMCID: PMC4319976  PMID: 22604722
2.  HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials 
Swerdlow, Daniel I | Preiss, David | Kuchenbaecker, Karoline B | Holmes, Michael V | Engmann, Jorgen E L | Shah, Tina | Sofat, Reecha | Stender, Stefan | Johnson, Paul C D | Scott, Robert A | Leusink, Maarten | Verweij, Niek | Sharp, Stephen J | Guo, Yiran | Giambartolomei, Claudia | Chung, Christina | Peasey, Anne | Amuzu, Antoinette | Li, KaWah | Palmen, Jutta | Howard, Philip | Cooper, Jackie A | Drenos, Fotios | Li, Yun R | Lowe, Gordon | Gallacher, John | Stewart, Marlene C W | Tzoulaki, Ioanna | Buxbaum, Sarah G | van der A, Daphne L | Forouhi, Nita G | Onland-Moret, N Charlotte | van der Schouw, Yvonne T | Schnabel, Renate B | Hubacek, Jaroslav A | Kubinova, Ruzena | Baceviciene, Migle | Tamosiunas, Abdonas | Pajak, Andrzej | Topor-Madry, Romanvan | Stepaniak, Urszula | Malyutina, Sofia | Baldassarre, Damiano | Sennblad, Bengt | Tremoli, Elena | de Faire, Ulf | Veglia, Fabrizio | Ford, Ian | Jukema, J Wouter | Westendorp, Rudi G J | de Borst, Gert Jan | de Jong, Pim A | Algra, Ale | Spiering, Wilko | der Zee, Anke H Maitland-van | Klungel, Olaf H | de Boer, Anthonius | Doevendans, Pieter A | Eaton, Charles B | Robinson, Jennifer G | Duggan, David | Kjekshus, John | Downs, John R | Gotto, Antonio M | Keech, Anthony C | Marchioli, Roberto | Tognoni, Gianni | Sever, Peter S | Poulter, Neil R | Waters, David D | Pedersen, Terje R | Amarenco, Pierre | Nakamura, Haruo | McMurray, John J V | Lewsey, James D | Chasman, Daniel I | Ridker, Paul M | Maggioni, Aldo P | Tavazzi, Luigi | Ray, Kausik K | Seshasai, Sreenivasa Rao Kondapally | Manson, JoAnn E | Price, Jackie F | Whincup, Peter H | Morris, Richard W | Lawlor, Debbie A | Smith, George Davey | Ben-Shlomo, Yoav | Schreiner, Pamela J | Fornage, Myriam | Siscovick, David S | Cushman, Mary | Kumari, Meena | Wareham, Nick J | Verschuren, W M Monique | Redline, Susan | Patel, Sanjay R | Whittaker, John C | Hamsten, Anders | Delaney, Joseph A | Dale, Caroline | Gaunt, Tom R | Wong, Andrew | Kuh, Diana | Hardy, Rebecca | Kathiresan, Sekar | Castillo, Berta A | van der Harst, Pim | Brunner, Eric J | Tybjaerg-Hansen, Anne | Marmot, Michael G | Krauss, Ronald M | Tsai, Michael | Coresh, Josef | Hoogeveen, Ronald C | Psaty, Bruce M | Lange, Leslie A | Hakonarson, Hakon | Dudbridge, Frank | Humphries, Steve E | Talmud, Philippa J | Kivimäki, Mika | Timpson, Nicholas J | Langenberg, Claudia | Asselbergs, Folkert W | Voevoda, Mikhail | Bobak, Martin | Pikhart, Hynek | Wilson, James G | Reiner, Alex P | Keating, Brendan J | Hingorani, Aroon D | Sattar, Naveed
Lancet  2015;385(9965):351-361.
Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target.
We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis.
Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05–0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18–0·43), waist circumference (0·32 cm, 0·16–0·47), plasma insulin concentration (1·62%, 0·53–2·72), and plasma glucose concentration (0·23%, 0·02–0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00–1·05); the rs12916-T allele association was consistent (1·06, 1·03–1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18–1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10–0·38 in all trials; 0·33 kg, 95% CI 0·24–0·42 in placebo or standard care controlled trials and −0·15 kg, 95% CI −0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9–6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06–1·18 in all trials; 1·11, 95% CI 1·03–1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04–1·22 in intensive-dose vs moderate dose trials).
The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition.
The funding sources are cited at the end of the paper.
PMCID: PMC4322187  PMID: 25262344
3.  Testing for non-linear causal effects using a binary genotype in a Mendelian randomization study: application to alcohol and cardiovascular traits 
Background: Mendelian randomization studies have so far restricted attention to linear associations relating the genetic instrument to the exposure, and the exposure to the outcome. In some cases, however, observational data suggest a non-linear association between exposure and outcome. For example, alcohol consumption is consistently reported as having a U-shaped association with cardiovascular events. In principle, Mendelian randomization could address concerns that the apparent protective effect of light-to-moderate drinking might reflect ‘sick-quitters’ and confounding.
Methods: The Alcohol-ADH1B Consortium was established to study the causal effects of alcohol consumption on cardiovascular events and biomarkers, using the single nucleotide polymorphism rs1229984 in ADH1B as a genetic instrument. To assess non-linear causal effects in this study, we propose a novel method based on estimating local average treatment effects for discrete levels of the exposure range, then testing for a linear trend in those effects. Our method requires an assumption that the instrument has the same effect on exposure in all individuals. We conduct simulations examining the robustness of the method to violations of this assumption, and apply the method to the Alcohol-ADH1B Consortium data.
Results: Our method gave a conservative test for non-linearity under realistic violations of the key assumption. We found evidence for a non-linear causal effect of alcohol intake on several cardiovascular traits.
Conclusions: We believe our method is useful for inferring departure from linearity when only a binary instrument is available. We estimated non-linear causal effects of alcohol intake which could not have been estimated through standard instrumental variable approaches.
PMCID: PMC4276061  PMID: 25192829
Mendelian randomization; instrumental variables; causal inference; local average treatment effects; alcohol consumption; cardiovascular disease
4.  Population Genomics of Cardiometabolic Traits: Design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium 
PLoS ONE  2013;8(8):e71345.
Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies.
PMCID: PMC3748096  PMID: 23977022
5.  Genetic association analysis of vitamin D pathway with obesity traits 
Observational studies have examined the link between vitamin D deficiency and obesity traits. Some studies have reported associations between vitamin D pathway genes such as VDR, GC and CYP27B1 with body mass index (BMI) and waist circumference (WC); however, the findings have been inconsistent. Hence, we investigated the involvement of vitamin D metabolic pathway genes in obesity-related traits in a large population-based study.
We undertook a comprehensive analysis between 100 tagging polymorphisms (tagSNPs) in genes encoding for DHCR7, CYP2R1, VDBP, CYP27B1, CYP27A1, CYP24A1, VDR and RXRG and obesity traits in 5,224 participants (aged 45 years) in the 1958 British birth cohort (1958BC). We further extended our analyses to investigate the associations between SNPs and obesity traits using the summary statistics from the GIANT (Genetic Investigation of Anthropometric Traits) consortium (n=123,865).
In the 1958BC (n=5,224), after Bonferroni correction, none of the tagSNPs were associated with obesity traits except for one tagSNP from CYP24A1 that was associated with waist-hip ratio (WHR) (rs2296239, P=0.001). However, the CYP24A1 SNP was not associated with BMI-adjusted WHR (WHRadj) in the 1958BC (rs2296239, P=1.00) and GIANT results (n=123,865, P=0.18). There was also no evidence for an interaction between the tagSNPs and obesity on BMI, WC, WHR and WHRadj in the 1958BC. In the GIANT consortium, none of the tagSNPs were associated with obesity traits.
Despite a very large study, our findings suggest that the vitamin D pathway genes are unlikely to have a major role in obesity-related traits in the general population.
PMCID: PMC3763965  PMID: 23381556
Vitamin D pathway; 1958 British birth cohort; tagSNPs; obesity; GIANT; BMI
6.  Potential Impact of Adding Genetic Markers to Clinical Parameters in Predicting Prostate Biopsy Outcomes in Men Following an Initial Negative Biopsy: Findings from the REDUCE Trial 
European urology  2012;62(6):953-961.
Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk.
To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa.
Design, setting, and participants
Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated.
Outcome measurements and statistical analysis
Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers.
Results and limitations
Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10−8). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p < 0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p = 0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥7) PCa. A major limitation of this study was its focus on white patients only.
Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.
PMCID: PMC3568765  PMID: 22652152
Prostate cancer; Genetics; AUC; Detection rate; Reclassification; SNPs; Prospective study; Clinical trial
7.  A Comparison of Bayesian and Frequentist Approaches to Incorporating External Information for the Prediction of Prostate Cancer Risk 
Genetic epidemiology  2012;36(1):71-83.
We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates – one via a weighted PCa ‘risk’ score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.
PMCID: PMC3791431  PMID: 22890972
prostate cancer; genetic clinical risk prediction; genetic scores; Bayesian logistic regression; predictive assessment
8.  The impact of targeting all elderly persons in England and Wales for yearly influenza vaccination: excess mortality due to pneumonia or influenza and time trend study 
BMJ Open  2013;3(8):e002743.
To investigate the impact on mortality due to pneumonia or influenza of the change from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales.
Excess mortality estimated using time series of deaths registered to pneumonia or influenza, accounting for seasonality, trend and artefacts. Non-excess mortality plotted as proxy for long-term trend in mortality.
England and Wales.
Persons aged 65–74 and 75+ years whose deaths were registered to underlying pneumonia or influenza between 1975/1976 and 2004/2005.
Outcome measures
Multiplicative effect on average excess pneumonia and influenza deaths each winter in the 4–6 winters since age group-based targeting of vaccination was introduced (in persons aged 75+ years from 1998/1999; in persons aged 65+ years from 2000/2001), estimated using multivariable regression adjusted for temperature, antigenic drift and vaccine mismatch, and stratified by dominant circulating influenza subtype. Trend in baseline weekly pneumonia and influenza death rates.
There is a suggestion of lower average excess mortality in the six winters after age group-based targeting began compared to before, but the CI for the 65–74 years age group includes no difference. Trend in baseline pneumonia and influenza mortality shows an apparent downward turning point around 2000 for the 65–74 years age group and from the mid-1990s in the 75+ years age group.
There is weakly supportive evidence that the marked increases in vaccine coverage accompanying the switch from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales were associated with lower levels of pneumonia and influenza mortality in older people in the first 6 years after age group-based targeting began. The possible impact of these policy changes is observed as weak evidence for lower average excess mortality as well as a turning point in baseline mortality coincident with the changes.
PMCID: PMC3733298  PMID: 23906952
Influenza; Mortality; Mass Vaccination; Aged; Trends
9.  Polymorphism at the TNF superfamily gene TNFSF4 confers susceptibility to systemic lupus erythematosus 
Nature genetics  2007;40(1):83-89.
Systemic lupus erythematosus (SLE) is a multisystem complex autoimmune disease of uncertain etiology (OMIM 152700). Over recent years a genetic component to SLE susceptibility has been established1–3. Recent successes with association studies in SLE have identified genes including IRF5 (refs. 4,5) and FCGR3B6. Two tumor necrosis factor (TNF) superfamily members located within intervals showing genetic linkage with SLE are TNFSF4 (also known as OX40L; 1q25), which is expressed on activated antigen-presenting cells (APCs)7,8 and vascular endothelial cells9, and also its unique receptor, TNFRSF4 (also known as OX40; 1p36), which is primarily expressed on activated CD4+ T cells10. TNFSF4 produces a potent co-stimulatory signal for activated CD4+ T cells after engagement of TNFRSF4 (ref. 11). Using both a family-based and a case-control study design, we show that the upstream region of TNFSF4 contains a single risk haplotype for SLE, which is correlated with increased expression of both cell-surface TNFSF4 and the TNFSF4 transcript. We hypothesize that increased expression of TNFSF4 predisposes to SLE either by quantitatively augmenting T cell–APC interaction or by influencing the functional consequences of T cell activation via TNFRSF4.
PMCID: PMC3705866  PMID: 18059267
10.  Deep sequencing of the LRRK2 gene in 14,002 individuals reveals evidence of purifying selection and independent origin of the p.Arg1628Pro mutation in Europe 
Human Mutation  2012;33(7):1087-1098.
Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single nucleotide variants (SNVs), 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Amongst Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.
PMCID: PMC3370131  PMID: 22415848
LRRK2; Deep sequencing; novel variants; evolution; population genetics; genotype-phenotype associations
11.  Association Between the Chromosome 9p21 Locus and Angiographic Coronary Artery Disease Burden 
This study sought to ascertain the relationship of 9p21 locus with: 1) angiographic coronary artery disease (CAD) burden; and 2) myocardial infarction (MI) in individuals with underlying CAD.
Chromosome 9p21 variants have been robustly associated with coronary heart disease, but questions remain on the mechanism of risk, specifically whether the locus contributes to coronary atheroma burden or plaque instability.
We established a collaboration of 21 studies consisting of 33,673 subjects with information on both CAD (clinical or angiographic) and MI status along with 9p21 genotype. Tabular data are provided for each cohort on the presence and burden of angiographic CAD, MI cases with underlying CAD, and the diabetic status of all subjects.
We first confirmed an association between 9p21 and CAD with angiographically defined cases and control subjects (pooled odds ratio [OR]: 1.31, 95% confidence interval [CI]: 1.20 to 1.43). Among subjects with angiographic CAD (n = 20,987), random-effects model identified an association with multivessel CAD, compared with those with single-vessel disease (OR: 1.10, 95% CI: 1.04 to 1.17)/copy of risk allele). Genotypic models showed an OR of 1.15, 95% CI: 1.04 to 1.26 for heterozygous carrier and OR: 1.23, 95% CI: 1.08 to 1.39 for homozygous carrier. Finally, there was no significant association between 9p21 and prevalent MI when both cases (n = 17,791) and control subjects (n = 15,882) had underlying CAD (OR: 0.99, 95% CI: 0.95 to 1.03)/risk allele.
The 9p21 locus shows convincing association with greater burden of CAD but not with MI in the presence of underlying CAD. This adds further weight to the hypothesis that 9p21 locus primarily mediates an atherosclerotic phenotype.
PMCID: PMC3653306  PMID: 23352782
9p21; angiography; coronary artery disease; meta-analysis; myocardial infarction; single nucleotide polymorphism
12.  Deep Resequencing Unveils Genetic Architecture of ADIPOQ and Identifies a Novel Low-Frequency Variant Strongly Associated With Adiponectin Variation 
Diabetes  2012;61(5):1297-1301.
Increased adiponectin levels have been shown to be associated with a lower risk of type 2 diabetes. To understand the relations between genetic variation at the adiponectin-encoding gene, ADIPOQ, and adiponectin levels, and subsequently its role in disease, we conducted a deep resequencing experiment of ADIPOQ in 14,002 subjects, including 12,514 Europeans, 594 African Americans, and 567 Indian Asians. We identified 296 single nucleotide polymorphisms (SNPs), including 30 amino acid changes, and carried out association analyses in a subset of 3,665 subjects from two independent studies. We confirmed multiple genome-wide association study findings and identified a novel association between a low-frequency SNP (rs17366653) and adiponectin levels (P = 2.2E–17). We show that seven SNPs exert independent effects on adiponectin levels. Together, they explained 6% of adiponectin variation in our samples. We subsequently assessed association between these SNPs and type 2 diabetes in the Genetics of Diabetes Audit and Research in Tayside Scotland (GO-DARTS) study, comprised of 5,145 case and 6,374 control subjects. No evidence of association with type 2 diabetes was found, but we were also unable to exclude the possibility of substantial effects (e.g., odds ratio 95% CI for rs7366653 [0.91–1.58]). Further investigation by large-scale and well-powered Mendelian randomization studies is warranted.
PMCID: PMC3331741  PMID: 22403302
13.  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.
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).
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
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
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 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
PMCID: PMC3564800  PMID: 23393431
14.  Comparison of Statistical Tests for Association between Rare Variants and Binary Traits 
PLoS ONE  2012;7(8):e42530.
Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait’s variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.
PMCID: PMC3415421  PMID: 22912707
15.  Evaluation of Genetic Markers as Instruments for Mendelian Randomization Studies on Vitamin D 
PLoS ONE  2012;7(5):e37465.
Mendelian randomization (MR) studies use genetic variants mimicking the influence of a modifiable exposure to assess and quantify a causal association with an outcome, with an aim to avoid problems with confounding and reverse causality affecting other types of observational studies.
We evaluated genetic markers that index differences in 25-hydroxyvitamin D (25(OH)D) as instruments for MR studies on vitamin D.
Methods and Findings
We used data from up-to 6,877 participants in the 1958 British birth cohort with information on genetic markers and 25(OH)D. As potential instruments, we selected 20 single nucleotide polymorphisms (SNP) which are located in the vitamin D metabolism pathway or affect skin pigmentation/tanning, including 4 SNPs from genome-wide association (GWA) meta-analyses on 25(OH)D. We analyzed SNP associations with 25(OH)D and evaluated the use of allele scores dividing genes to those affecting 25(OH)D synthesis (DHCR7, CYP2R1) and metabolism (GC, CYP24A1, CYP27B1). In addition to the GWA SNPs, only two SNPs (CYP27B1, OCA2) showed evidence for association with 25(OH)D, with the OCA2 association abolished after lifestyle adjustment. Per allele differences varied between −0.02 and −0.08 nmol/L (P≤0.02 for all), with a 6.1 nmol/L and a 10.2 nmol/L difference in 25(OH)D between individuals with highest compared lowest number of risk alleles in synthesis and metabolism allele scores, respectively. Individual SNPs but not allele scores showed associations with lifestyle factors. An exception was geographical region which was associated with synthesis score. Illustrative power calculations (80% power, 5% alpha) suggest that approximately 80,000 participants are required to establish a causal effect of vitamin D on blood pressure using the synthesis allele score.
Combining SNPs into allele scores provides a more powerful instrument for MR analysis than a single SNP in isolation. Population stratification and the potential for pleiotropic effects need to be considered in MR studies on vitamin D.
PMCID: PMC3357436  PMID: 22629401
16.  Performance of Genotype Imputation for Rare Variants Identified in Exons and Flanking Regions of Genes 
PLoS ONE  2011;6(9):e24945.
Genotype imputation has the potential to assess human genetic variation at a lower cost than assaying the variants using laboratory techniques. The performance of imputation for rare variants has not been comprehensively studied. We utilized 8865 human samples with high depth resequencing data for the exons and flanking regions of 202 genes and Genome-Wide Association Study (GWAS) data to characterize the performance of genotype imputation for rare variants. We evaluated reference sets ranging from 100 to 3713 subjects for imputing into samples typed for the Affymetrix (500K and 6.0) and Illumina 550K GWAS panels. The proportion of variants that could be well imputed (true r2>0.7) with a reference panel of 3713 individuals was: 31% (Illumina 550K) or 25% (Affymetrix 500K) with MAF (Minor Allele Frequency) less than or equal 0.001, 48% or 35% with 0.0010.05. The performance for common SNPs (MAF>0.05) within exons and flanking regions is comparable to imputation of more uniformly distributed SNPs. The performance for rare SNPs (0.01
PMCID: PMC3176314  PMID: 21949800
European Journal of Human Genetics  2010;18(9):1027-1031.
The Fcγ-receptor locus on chromosome 1q23 shows copy-number variation (CNV), and it has previously been shown that individuals with reduced numbers of copies of the Fcγ-receptor-IIIB gene (FCGR3B) have an increased risk of developing systemic lupus erythematosus (SLE). It is not understood whether the association arises from FCGR3B (CD16b) itself, is observed because of linkage disequilibrium with actual causal alleles and/or is an effect of CNV on flanking FCGR genes. Thus, we extended this previous work by genotyping the FCGR3B alleles NA1/NA2 and re-assaying CNV using a paralogue ratio test assay in a family study (365 families). We have developed a novel case/pseudo-control approach to analyse family data, as the phase of copy number (CN) is not known in parents and cannot always be inferred in offspring. The results, obtained by fitting logistic regression models, confirm the association of low CN of FCGR3B with SLE (P=0.04). The risk conferred by low copies (<2) was contingent on FCGR3B allotype, being greater for deletion of NA1 than the for lower-affinity NA2. The simpler model with just CN was rejected in favour of the biallelic-CN model (P=0.03). We observed a correlation (R2=0.75, P<0.0001) between FCGR3B CNV and neutrophil expression in both healthy controls and patients with SLE. Our results suggest that one mechanism by which CNV at this locus confers disease risk is directly as a result of reduced FcγRIIIb function, either because of reduced expression (related to CNV) or because of reduced affinity for its ligand (NA1/NA2 allotype).
PMCID: PMC2987408  PMID: 20442749
FCGR3B; NA1/NA2; genetics; systemic lupus erythematosus; CNV
Lancet  2011;378(9791):584-594.
The MTHFR 677C→T polymorphism has been associated with raised homocysteine concentration and increased risk of stroke. A previous overview showed that the effects were greatest in regions with low dietary folate consumption, but differentiation between the effect of folate and small-study bias was difficult. A meta-analysis of randomised trials of homocysteine-lowering interventions showed no reduction in coronary heart disease events or stroke, but the trials were generally set in populations with high folate consumption. We aimed to reduce the effect of small-study bias and investigate whether folate status modifies the association between MTHFR 677C→T and stroke in a genetic analysis and meta-analysis of randomised controlled trials.
We established a collaboration of genetic studies consisting of 237 datasets including 59 995 individuals with data for homocysteine and 20 885 stroke events. We compared the genetic findings with a meta-analysis of 13 randomised trials of homocysteine-lowering treatments and stroke risk (45 549 individuals, 2314 stroke events, 269 transient ischaemic attacks).
The effect of the MTHFR 677C→T variant on homocysteine concentration was larger in low folate regions (Asia; difference between individuals with TT versus CC genotype, 3·12 μmol/L, 95% CI 2·23 to 4·01) than in areas with folate fortification (America, Australia, and New Zealand, high; 0·13 μmol/L, −0·85 to 1·11). The odds ratio (OR) for stroke was also higher in Asia (1·68, 95% CI 1·44 to 1·97) than in America, Australia, and New Zealand, high (1·03, 0·84 to 1·25). Most randomised trials took place in regions with high or increasing population folate concentrations. The summary relative risk (RR) of stroke in trials of homocysteine-lowering interventions (0·94, 95% CI 0·85 to 1·04) was similar to that predicted for the same extent of homocysteine reduction in large genetic studies in populations with similar folate status (predicted RR 1·00, 95% CI 0·90 to 1·11). Although the predicted effect of homocysteine reduction from large genetic studies in low folate regions (Asia) was larger (RR 0·78, 95% CI 0·68 to 0·90), no trial has evaluated the effect of lowering of homocysteine on stroke risk exclusively in a low folate region.
In regions with increasing levels or established policies of population folate supplementation, evidence from genetic studies and randomised trials is concordant in suggesting an absence of benefit from lowering of homocysteine for prevention of stroke. Further large-scale genetic studies of the association between MTHFR 677C→T and stroke in low folate settings are needed to distinguish effect modification by folate from small-study bias. If future randomised trials of homocysteine-lowering interventions for stroke prevention are undertaken, they should take place in regions with low folate consumption.
Full funding sources listed at end of paper (see Acknowledgments).
PMCID: PMC3156981  PMID: 21803414
European Heart Journal  2011;33(3):393-407.
To evaluate the associations of emergent genome-wide-association study-derived coronary heart disease (CHD)-associated single nucleotide polymorphisms (SNPs) with established and emerging risk factors, and the association of genome-wide-association study-derived lipid-associated SNPs with other risk factors and CHD events.
Methods and results
Using two case–control studies, three cross-sectional, and seven prospective studies with up to 25 000 individuals and 5794 CHD events we evaluated associations of 34 genome-wide-association study-identified SNPs with CHD risk and 16 CHD-associated risk factors or biomarkers. The Ch9p21 SNPs rs1333049 (OR 1.17; 95% confidence limits 1.11–1.24) and rs10757274 (OR 1.17; 1.09–1.26), MIA3 rs17465637 (OR 1.10; 1.04–1.15), Ch2q36 rs2943634 (OR 1.08; 1.03–1.14), APC rs383830 (OR 1.10; 1.02, 1.18), MTHFD1L rs6922269 (OR 1.10; 1.03, 1.16), CXCL12 rs501120 (OR 1.12; 1.04, 1.20), and SMAD3 rs17228212 (OR 1.11; 1.05, 1.17) were all associated with CHD risk, but not with the CHD biomarkers and risk factors measured. Among the 20 blood lipid-related SNPs, LPL rs17411031 was associated with a lower risk of CHD (OR 0.91; 0.84–0.97), an increase in Apolipoprotein AI and HDL-cholesterol, and reduced triglycerides. SORT1 rs599839 was associated with CHD risk (OR 1.20; 1.15–1.26) as well as total- and LDL-cholesterol, and apolipoprotein B. ANGPTL3 rs12042319 was associated with CHD risk (OR 1.11; 1.03, 1.19), total- and LDL-cholesterol, triglycerides, and interleukin-6.
Several SNPs predicting CHD events appear to involve pathways not currently indexed by the established or emerging risk factors; others involved changes in blood lipids including triglycerides or HDL-cholesterol as well as LDL-cholesterol. The overlapping association of SNPs with multiple risk factors and biomarkers supports the existence of shared points of regulation for these phenotypes.
PMCID: PMC3270041  PMID: 21804106
Coronary disease; Lipids; Genes; Risk factors
Based on published data, this ecological correlation study showed evidence to support the hypothesis that variation in the risk allele frequency of the Y402H polymorphism across ethnicities explains variation in prevalence of late AMD when data on people of African ancestry are excluded.
To investigate whether variation in the distribution of the risk allele frequency of the Y402H single-nucleotide polymorphism (SNP) across various ethnicities and geographic regions reflects differences in the prevalence of late age-related macular degeneration (AMD) in those ethnicities.
Published data were obtained via a systematic search. Study samples were grouped into clusters by ethnicity and geographic location and the Spearman correlation coefficient of the prevalence of late AMD and risk allele frequencies was calculated across clusters.
Across all ethnicities, AMD prevalence was seen to increase with age. Populations of European descent had both higher risk allele frequencies and prevalence of late AMD than did Japanese, Chinese, and Hispanic descendants. Results for African descendants were anomalous: although allele frequency was similar to that in European populations, the age-specific prevalence of late AMD was considerably lower. The correlation coefficient for the association between allele frequency and AMD prevalence was 0.40 (95% confidence interval [CI] = −0.36 to 0.84, P = 0.28) in all populations combined and 0.71 (95% CI = 0.02–0.94, P = 0.04) when people of African descent were excluded.
Evidence was found at the population level to support a positive association between the Y204H risk allele and the prevalence of AMD after exclusion of studies undertaken on persons of African ancestry. Data in African, Middle Eastern, and South American populations are needed to provide a better understanding of the association of late AMD genetic risk across ethnicities.
PMCID: PMC2868481  PMID: 20042653
Human genetics  2008;123(6):633-642.
Basal levels of C-reactive protein (CRP) have been associated with disease, particularly future cardiovascular events. Twin studies estimate 50% CRP heritability, so the identification of genetic variants influencing CRP expression is important. Existing studies in populations of European ancestry have identified numerous cis-acting variants but leave significant ambiguity over the identity of the key functional polymorphisms. We addressed this issue by typing a dense map of CRP single nucleotide polymorphisms (SNPs), and quantifying serum CRP in 594 unrelated African Americans. We used Bayesian model choice analysis to select the combination of SNPs best explaining basal CRP and found strong support for triallelic rs3091244 alone, with the T allele acting in an additive manner (Bayes factor >100 vs. null model), with additional support for a model incorporating both rs3091244 and rs12728740. Admixture analysis suggested SNP rs12728740 segregated with haplotypes predicted to be of recent European origin. Using a cladistic approach we confirmed the importance of rs3091244(T) by demonstrating a significant partition of haplotype effect based on the rs3091244(C/T) mutation (F=8.91, P=0.006). We argue that weaker linkage disequilibrium across the African American CRP locus compared with Europeans has allowed us to establish an unambiguous functional role for rs3091244(T), while also recognising the potential for additional functional mutations present in the European genome.
PMCID: PMC2630773  PMID: 18500540
C-reactive protein; African Americans; quantitative trait analysis; Bayesian statistics; racial admixture; genetics
Lancet Neurology  2009;8(1):57-66.
Human and animal prion diseases are under genetic control, but apart from PRNP (the gene that encodes the prion protein), we understand little about human susceptibility to bovine spongiform encephalopathy (BSE) prions, the causal agent of variant Creutzfeldt–Jakob disease (vCJD).
We did a genome-wide association study of the risk of vCJD and tested for replication of our findings in samples from many categories of human prion disease (929 samples) and control samples from the UK and Papua New Guinea (4254 samples), including controls in the UK who were genotyped by the Wellcome Trust Case Control Consortium. We also did follow-up analyses of the genetic control of the clinical phenotype of prion disease and analysed candidate gene expression in a mouse cellular model of prion infection.
The PRNP locus was strongly associated with risk across several markers and all categories of prion disease (best single SNP [single nucleotide polymorphism] association in vCJD p=2·5×10−17; best haplotypic association in vCJD p=1×10−24). Although the main contribution to disease risk was conferred by PRNP polymorphic codon 129, another nearby SNP conferred increased risk of vCJD. In addition to PRNP, one technically validated SNP association upstream of RARB (the gene that encodes retinoic acid receptor beta) had nominal genome-wide significance (p=1·9×10−7). A similar association was found in a small sample of patients with iatrogenic CJD (p=0·030) but not in patients with sporadic CJD (sCJD) or kuru. In cultured cells, retinoic acid regulates the expression of the prion protein. We found an association with acquired prion disease, including vCJD (p=5·6×10−5), kuru incubation time (p=0·017), and resistance to kuru (p=2·5×10−4), in a region upstream of STMN2 (the gene that encodes SCG10). The risk genotype was not associated with sCJD but conferred an earlier age of onset. Furthermore, expression of Stmn2 was reduced 30-fold post-infection in a mouse cellular model of prion disease.
The polymorphic codon 129 of PRNP was the main genetic risk factor for vCJD; however, additional candidate loci have been identified, which justifies functional analyses of these biological pathways in prion disease.
The UK Medical Research Council.
PMCID: PMC2643048  PMID: 19081515
BMC Bioinformatics  2008;9:364.
FREGENE simulates sequence-level data over large genomic regions in large populations. Because, unlike coalescent simulators, it works forwards through time, it allows complex scenarios of selection, demography, and recombination to be modelled simultaneously. Detailed tracking of sites under selection is implemented in FREGENE and provides the opportunity to test theoretical predictions and gain new insights into mechanisms of selection. We describe here main functionalities of both FREGENE and SAMPLE, a companion program that can replicate association study datasets.
We report detailed analyses of six large simulated datasets that we have made publicly available. Three demographic scenarios are modelled: one panmictic, one substructured with migration, and one complex scenario that mimics the principle features of genetic variation in major worldwide human populations. For each scenario there is one neutral simulation, and one with a complex pattern of selection.
FREGENE and the simulated datasets will be valuable for assessing the validity of models for selection, demography and population genetic parameters, as well as the efficacy of association studies. Its principle advantages are modelling flexibility and computational efficiency. It is open source and object-oriented. As such, it can be customised and the range of models extended.
PMCID: PMC2542380  PMID: 18778480
PLoS Genetics  2008;4(7):e1000130.
Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re-sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation.
Author Summary
Tests of association with disease status are normally conducted one SNP at a time, ignoring the effects of all other genotyped SNPs. We developed a computationally efficient method to simultaneously analyse all SNPs, either in a genome-wide association (GWA) study, or a fine-mapping study based on re-sequencing and/or imputation. The method selects a subset of SNPs that best predicts disease status, while controlling the type-I error of the selected SNPs. This brings many advantages over standard single-SNP approaches, because the signal from a particular SNP can be more clearly assessed when other SNPs associated with disease status are already included in the model. Thus, in comparison with single-SNP analyses, power is increased and the false positive rate is reduced because of reduced residual variation. Localisation is also greatly improved. We demonstrate these advantages over the widely used single-SNP Armitage Trend Test using GWA simulation studies, a real GWA dataset, and a sequence-based fine-mapping simulation study.
PMCID: PMC2464715  PMID: 18654633
BMJ : British Medical Journal  2007;334(7598):833.
Objectives To determine if the risks of perinatal mortality and antepartum stillbirth associated with post term birth increase earlier during pregnancy in South Asian and black women than in white women, and to investigate differences in the factors associated with antepartum stillbirth between the racial groups.
Design Prospective study using logistic regression analysis.
Setting 15 maternity units in northwest London from 1988 to 2000.
Participants 197 061 nulliparous women self reported as white, South Asian, or black, who delivered a single baby weighing at least 500 g at 24-43 completed weeks' gestation.
Main outcome measures Gestation specific perinatal mortality, antepartum stillbirth rates, and independent factors for antepartum stillbirth by racial groups.
Results The crude gestation specific perinatal mortality patterns for the three racial groups differed (P<0.001). The perinatal mortality rate among black women was lower than among white women before 32 weeks but was higher thereafter. Perinatal mortality was highest among South Asian women at all gestational ages and increased the fastest at term. After adjusting for the confounders of antepartum stillbirth (placental abruption, congenital abnormality, low birth weight, birth weight <10th centile, meconium passage, fever, maternal body mass index ≥30, and maternal age ≥30), the excess mortality among black women after 32 weeks was not significant. After adjusting for confounding, South Asian women still had a significantly higher risk of antepartum stillbirth (odds ratio 1.8, 95% confidence interval 1.2 to 2.7).
Conclusions The risk of perinatal mortality increased earlier in gestation among South Asian women than among white women. The most important factor associated with antepartum stillbirth among white women was placental abruption, but among South Asian and black women it was birth weight below 2000 g.
PMCID: PMC1853199  PMID: 17337455

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