Publications by authors named "Audrey E Hendricks"

40 Publications

Summix: A method for detecting and adjusting for population structure in genetic summary data.

Am J Hum Genet 2021 07 21;108(7):1270-1282. Epub 2021 Jun 21.

Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA; Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO 80045, USA. Electronic address:

Publicly available genetic summary data have high utility in research and the clinic, including prioritizing putative causal variants, polygenic scoring, and leveraging common controls. However, summarizing individual-level data can mask population structure, resulting in confounding, reduced power, and incorrect prioritization of putative causal variants. This limits the utility of publicly available data, especially for understudied or admixed populations where additional research and resources are most needed. Although several methods exist to estimate ancestry in individual-level data, methods to estimate ancestry proportions in summary data are lacking. Here, we present Summix, a method to efficiently deconvolute ancestry and provide ancestry-adjusted allele frequencies (AFs) from summary data. Using continental reference ancestry, African (AFR), non-Finnish European (EUR), East Asian (EAS), Indigenous American (IAM), South Asian (SAS), we obtain accurate and precise estimates (within 0.1%) for all simulation scenarios. We apply Summix to gnomAD v.2.1 exome and genome groups and subgroups, finding heterogeneous continental ancestry for several groups, including African/African American (∼84% AFR, ∼14% EUR) and American/Latinx (∼4% AFR, ∼5% EAS, ∼43% EUR, ∼46% IAM). Compared to the unadjusted gnomAD AFs, Summix's ancestry-adjusted AFs more closely match respective African and Latinx reference samples. Even on modern, dense panels of summary statistics, Summix yields results in seconds, allowing for estimation of confidence intervals via block bootstrap. Given an accompanying R package, Summix increases the utility and equity of public genetic resources, empowering novel research opportunities.
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http://dx.doi.org/10.1016/j.ajhg.2021.05.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322937PMC
July 2021

Improved first trimester maternal iodine status with preconception supplementation: The Women First Trial.

Matern Child Nutr 2021 10 25;17(4):e13204. Epub 2021 May 25.

Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, Colorado, USA.

Maternal iodine (I) status is critical in embryonic and foetal development. We examined the effect of preconception iodine supplementation on maternal iodine status and on birth outcomes. Non-pregnant women in Guatemala, India and Pakistan (n ~ 100 per arm per site) were randomized ≥ 3 months prior to conception to one of three intervention arms: a multimicronutrient-fortified lipid-based nutrient supplement containing 250-μg I per day started immediately after randomization (Arm 1), the same supplement started at ~12 weeks gestation (Arm 2) and no intervention supplement (Arm 3). Urinary I (μg/L) to creatinine (mg/dl) ratios (I/Cr) were determined at 12 weeks for Arm 1 versus Arm 2 (before supplement started) and 34 weeks for all arms. Generalized linear models were used to assess the relationship of I/Cr with arm and with newborn anthropometry. At 12 weeks gestation, adjusted mean I/Cr (μg/g) for all sites combined was significantly higher for Arm 1 versus Arm 2: (203 [95% CI: 189, 217] vs. 163 [95% CI: 152, 175], p < 0.0001). Overall adjusted prevalence of I/Cr < 150 μg/g was also lower in Arm 1 versus Arm 2: 32% (95% CI: 26%, 38%) versus 43% (95% CI: 37%, 49%) (p = 0.0052). At 34 weeks, adjusted mean I/Cr for Arm 1 (235, 95% CI: 220, 252) and Arm 2 (254, 95% CI: 238, 272) did not differ significantly but were significantly higher than Arm 3 (200, 95% CI: 184, 218) (p < 0.0001). Nominally significant positive associations were observed between I/Cr at 12 weeks and birth length and head circumference z-scores (p = 0.028 and p = 0.005, respectively). These findings support the importance of first trimester iodine status and suggest need for preconception supplementation beyond salt iodization alone.
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http://dx.doi.org/10.1111/mcn.13204DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476419PMC
October 2021

Genome-wide copy number variations in a large cohort of bantu African children.

BMC Med Genomics 2021 05 17;14(1):129. Epub 2021 May 17.

Department of Pediatrics, University of Colorado School of Medicine, Aurora, USA.

Background: Copy number variations (CNVs) account for a substantial proportion of inter-individual genomic variation. However, a majority of genomic variation studies have focused on single-nucleotide variations (SNVs), with limited genome-wide analysis of CNVs in large cohorts, especially in populations that are under-represented in genetic studies including people of African descent.

Methods: We carried out a genome-wide copy number analysis in > 3400 healthy Bantu Africans from Tanzania. Signal intensity data from high density (> 2.5 million probes) genotyping arrays were used for CNV calling with three algorithms including PennCNV, DNAcopy and VanillaICE. Stringent quality metrics and filtering criteria were applied to obtain high confidence CNVs.

Results: We identified over 400,000 CNVs larger than 1 kilobase (kb), for an average of 120 CNVs (SE = 2.57) per individual. We detected 866 large CNVs (≥ 300 kb), some of which overlapped genomic regions previously associated with multiple congenital anomaly syndromes, including Prader-Willi/Angelman syndrome (Type1) and 22q11.2 deletion syndrome. Furthermore, several of the common CNVs seen in our cohort (≥ 5%) overlap genes previously associated with developmental disorders.

Conclusions: These findings may help refine the phenotypic outcomes and penetrance of variations affecting genes and genomic regions previously implicated in diseases. Our study provides one of the largest datasets of CNVs from individuals of African ancestry, enabling improved clinical evaluation and disease association of CNVs observed in research and clinical studies in African populations.
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http://dx.doi.org/10.1186/s12920-021-00978-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130444PMC
May 2021

Lipidomics-Based Comparison of Molecular Compositions of Green, Yellow, and Red Bell Peppers.

Metabolites 2021 Apr 14;11(4). Epub 2021 Apr 14.

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO 80045, USA.

Identifying and annotating the molecular composition of individual foods will improve scientific understanding of how foods impact human health and how much variation exists in the molecular composition of foods of the same species. The complexity of this task includes distinct varieties and variations in natural occurring pigments of foods. Lipidomics, a sub-field of metabolomics, has emerged as an effective tool to help decipher the molecular composition of foods. For this proof-of-principle research, we determined the lipidomic profiles of green, yellow and red bell peppers () using liquid chromatography mass spectrometry and a novel tool for automated annotation of compounds following database searches. Among 23 samples analyzed from 6 peppers (2 green, 1 yellow, and 3 red), over 8000 lipid compounds were detected with 315 compounds (106 annotated) found in all three colors. Assessments of relationships between these compounds and pepper color, using linear mixed effects regression and false discovery rate (<0.05) statistical adjustment, revealed 11 compounds differing by color. The compound most strongly associated with color was the carotenoid, β-cryptoxanthin (-value = 7.4 × 10; FDR adjusted -value = 0.0080). These results support lipidomics as a viable analytical technique to identify molecular compounds that can be used for unique characterization of foods.
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http://dx.doi.org/10.3390/metabo11040241DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8070949PMC
April 2021

Different Blood Metabolomics Profiles in Infants Consuming a Meat- or Dairy-Based Complementary Diet.

Nutrients 2021 Jan 27;13(2). Epub 2021 Jan 27.

Section of Nutrition, Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

Background: Research is limited in evaluating the mechanisms responsible for infant growth in response to different protein-rich foods; Methods: Targeted and untargeted metabolomics analysis were conducted on serum samples collected from an infant controlled-feeding trial that participants consumed a meat- vs. dairy-based complementary diet from 5 to 12 months of age, and followed up at 24 months.

Results: Isoleucine, valine, phenylalanine increased and threonine decreased over time among all participants; Although none of the individual essential amino acids had a significant impact on changes in growth Z scores from 5 to 12 months, principal component heavily weighted by BCAAs (leucine, isoleucine, valine) and phenylalanine had a positive association with changes in length-for-age Z score from 5 to 12 months. Concentrations of acylcarnitine-C4, acylcarnitine-C5 and acylcarnitine-C5:1 significantly increased over time with the dietary intervention, but none of the acylcarnitines were associated with infant growth Z scores. Quantitative trimethylamine N-oxide increased in the meat group from 5 to 12 months; Conclusions: Our findings suggest that increasing total protein intake by providing protein-rich complementary foods was associated with increased concentrations of certain essential amino acids and short-chain acyl-carnitines. The sources of protein-rich foods (e.g., meat vs. dairy) did not appear to differentially impact serum metabolites, and comprehensive mechanistic investigations are needed to identify other contributors or mediators of the diet-induced infant growth trajectories.
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http://dx.doi.org/10.3390/nu13020388DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912106PMC
January 2021

Exome Sequencing Identifies Genes and Gene Sets Contributing to Severe Childhood Obesity, Linking PHIP Variants to Repressed POMC Transcription.

Cell Metab 2020 06;31(6):1107-1119.e12

Wellcome Sanger Institute, Cambridge, UK; University of Cambridge MRC Epidemiology Unit, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK. Electronic address:

Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome and targeted sequencing in 2,737 severely obese cases and 6,704 controls, we identified three genes (PHIP, DGKI, and ZMYM4) with an excess burden of very rare predicted deleterious variants in cases. In cells, we found that nuclear PHIP (pleckstrin homology domain interacting protein) directly enhances transcription of pro-opiomelanocortin (POMC), a neuropeptide that suppresses appetite. Obesity-associated PHIP variants repressed POMC transcription. Our demonstration that PHIP is involved in human energy homeostasis through transcriptional regulation of central melanocortin signaling has potential diagnostic and therapeutic implications for patients with obesity and developmental delay. Additionally, we found an excess burden of predicted deleterious variants involving genes nearest to loci from obesity genome-wide association studies. Genes and gene sets influencing obesity with variable penetrance provide compelling evidence for a continuum of causality in the genetic architecture of obesity, and explain some of its missing heritability.
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http://dx.doi.org/10.1016/j.cmet.2020.05.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267775PMC
June 2020

Longitudinal Changes of One-Carbon Metabolites and Amino Acid Concentrations during Pregnancy in the Women First Maternal Nutrition Trial.

Curr Dev Nutr 2020 Jan 18;4(1):nzz132. Epub 2019 Nov 18.

Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Background: Maternal dietary restriction and supplementation of one-carbon (1C) metabolites can impact offspring growth and DNA methylation. However, longitudinal research of 1C metabolite and amino acid (AA) concentrations over the reproductive cycle of human pregnancy is limited.

Objective: To investigate longitudinal 1C metabolite and AA concentrations prior to and during pregnancy and the effects of a small-quantity lipid-based nutrition supplement (LNS) containing >20 micronutrients and prepregnancy BMI (ppBMI).

Methods: This study was an ancillary study of the Women First Trial (NCT01883193, clinicaltrials.gov) focused on a subset of Guatemalan women ( = 134), 49% of whom entered pregnancy with a BMI ≥25 kg/m. Ninety-five women received LNS during pregnancy (+LNS group), while the remainder did not (-LNS group). A subset of women from the Pakistan study site ( = 179) were used as a replication cohort, 124 of whom received LNS. Maternal blood was longitudinally collected on dried blood spot (DBS) cards at preconception, and at 12 and 34 wk gestation. A targeted metabolomics assay was performed on DBS samples at each time point using LC-MS/MS. Longitudinal analyses were performed using linear mixed modeling to investigate the influence of time, LNS, and ppBMI.

Results: Concentrations of 23 of 27 metabolites, including betaine, choline, and serine, changed from preconception across gestation after application of a Bonferroni multiple testing correction ( < 0.00185). Sixteen of those metabolites showed similar changes in the replication cohort. Asymmetric and symmetric dimethylarginine were decreased by LNS in the participants from Guatemala. Only tyrosine was statistically associated with ppBMI at both study sites.

Conclusions: Time influenced most 1C metabolite and AA concentrations with a high degree of similarity between the 2 diverse study populations. These patterns were not significantly altered by LNS consumption or ppBMI. Future investigations will focus on 1C metabolite changes associated with infant outcomes, including DNA methylation. This trial was registered at clinicaltrials.gov as NCT01883193.
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http://dx.doi.org/10.1093/cdn/nzz132DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064164PMC
January 2020

Nutrimetabolomics reveals food-specific compounds in urine of adults consuming a DASH-style diet.

Sci Rep 2020 01 24;10(1):1157. Epub 2020 Jan 24.

Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, 12700 E 19th Avenue, Aurora, CO, 80045, USA.

Although health benefits of the Dietary Approaches to Stop Hypertension (DASH) diet are established, it is not understood which food compounds result in these benefits. We used metabolomics to identify unique compounds from individual foods of a DASH-style diet and determined if these Food-Specific Compounds (FSC) are detectable in urine from participants in a DASH-style dietary study. We also examined relationships between urinary compounds and blood pressure (BP). Nineteen subjects were randomized into 6-week controlled DASH-style diet interventions. Mass spectrometry-based metabolomics was performed on 24-hour urine samples collected before and after each intervention and on 12 representative DASH-style foods. Between 66-969 compounds were catalogued as FSC; for example, 4-hydroxydiphenylamine was found to be unique to apple. Overall, 13-190 of these FSC were detected in urine, demonstrating that these unmetabolized food compounds can be discovered in urine using metabolomics. Although linear mixed effects models showed no FSC from the 12 profiled foods were significantly associated with BP, other endogenous and food-related compounds were associated with BP (N = 16) and changes in BP over time (N = 6). Overall, this proof of principle study demonstrates that metabolomics can be used to catalog FSC, which can be detected in participant urine following a dietary intervention.
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http://dx.doi.org/10.1038/s41598-020-57979-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981146PMC
January 2020

Different Gut Microbial Profiles in Sub-Saharan African and South Asian Women of Childbearing Age Are Primarily Associated With Dietary Intakes.

Front Microbiol 2019 14;10:1848. Epub 2019 Aug 14.

Section of Nutrition, Department of Pediatrics, University of Colorado Denver, Aurora, CO, United States.

Background: To compare and characterize the gut microbiota in women of childbearing age from sub-Saharan Africa (the Democratic Republic of the Congo, DRC) and South Asia (India), in relation to dietary intakes.

Methods: Women of childbearing age were recruited from rural DRC and India as part of the Women First (WF) preconception maternal nutrition trial. Findings presented include fecal 16S rRNA gene-based profiling of women in the WF trial from samples obtained at the time of randomization, prior to initiation of nutrition intervention and to conception.

Results: Stool samples were collected from 217 women (DRC = 117; India = 100). Alpha diversity of the gut microbiota was higher in DRC than in India (Chao1: 91 ± 11 vs. 82 ± 12, = 6.58E-07). The gut microbial community structure was not significantly affected by any demographical or environmental variables, such as maternal BMI, education, and water source. , and were at relatively high abundance without differences between sites. was higher in India (4.95 ± 1.0%) than DRC (0.3 ± 0.1%; = 2.71E-27), as was (DRC: 0.2 ± 0.0%; India: 1.2 ± 0.1%; = 2.39E-13) and (DRC: 6.0 ± 1.7%; India: 8.4 ± 2.9%; = 6.51E-7). was higher in DRC (2.3 ± 0.7%) than in India (1.8 ± 0.4%; = 3.24E-5) and was positively associated with consumption of flesh foods. was positively associated with dairy intake in India and fish/insects in DRC. was positively associated with vitamin A-rich fruits and vegetables. Overall, these observations were consistent with India being primarily vegetarian with regular fermented dairy consumption and DRC regularly consuming animal-flesh foods.

Conclusion: Consumption of animal-flesh foods and fermented dairy foods were independently associated with the gut microbiota while demographic variables were not, suggesting that diet may have a stronger association with microbiota than demographic characteristics.
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http://dx.doi.org/10.3389/fmicb.2019.01848DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702451PMC
August 2019

Steroid receptor coactivator-1 modulates the function of Pomc neurons and energy homeostasis.

Nat Commun 2019 04 12;10(1):1718. Epub 2019 Apr 12.

Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.

Hypothalamic neurons expressing the anorectic peptide Pro-opiomelanocortin (Pomc) regulate food intake and body weight. Here, we show that Steroid Receptor Coactivator-1 (SRC-1) interacts with a target of leptin receptor activation, phosphorylated STAT3, to potentiate Pomc transcription. Deletion of SRC-1 in Pomc neurons in mice attenuates their depolarization by leptin, decreases Pomc expression and increases food intake leading to high-fat diet-induced obesity. In humans, fifteen rare heterozygous variants in SRC-1 found in severely obese individuals impair leptin-mediated Pomc reporter activity in cells, whilst four variants found in non-obese controls do not. In a knock-in mouse model of a loss of function human variant (SRC-1), leptin-induced depolarization of Pomc neurons and Pomc expression are significantly reduced, and food intake and body weight are increased. In summary, we demonstrate that SRC-1 modulates the function of hypothalamic Pomc neurons, and suggest that targeting SRC-1 may represent a useful therapeutic strategy for weight loss.
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http://dx.doi.org/10.1038/s41467-019-08737-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461669PMC
April 2019

Human Semaphorin 3 Variants Link Melanocortin Circuit Development and Energy Balance.

Cell 2019 02 17;176(4):729-742.e18. Epub 2019 Jan 17.

University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK. Electronic address:

Hypothalamic melanocortin neurons play a pivotal role in weight regulation. Here, we examined the contribution of Semaphorin 3 (SEMA3) signaling to the development of these circuits. In genetic studies, we found 40 rare variants in SEMA3A-G and their receptors (PLXNA1-4; NRP1-2) in 573 severely obese individuals; variants disrupted secretion and/or signaling through multiple molecular mechanisms. Rare variants in this set of genes were significantly enriched in 982 severely obese cases compared to 4,449 controls. In a zebrafish mutagenesis screen, deletion of 7 genes in this pathway led to increased somatic growth and/or adiposity demonstrating that disruption of Semaphorin 3 signaling perturbs energy homeostasis. In mice, deletion of the Neuropilin-2 receptor in Pro-opiomelanocortin neurons disrupted their projections from the arcuate to the paraventricular nucleus, reduced energy expenditure, and caused weight gain. Cumulatively, these studies demonstrate that SEMA3-mediated signaling drives the development of hypothalamic melanocortin circuits involved in energy homeostasis.
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http://dx.doi.org/10.1016/j.cell.2018.12.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370916PMC
February 2019

Body mass index is negatively associated with telomere length: a collaborative cross-sectional meta-analysis of 87 observational studies.

Am J Clin Nutr 2018 09;108(3):453-475

Department of Epidemiology and Public Health, University College London, London, United Kingdom.

Background: Even before the onset of age-related diseases, obesity might be a contributing factor to the cumulative burden of oxidative stress and chronic inflammation throughout the life course. Obesity may therefore contribute to accelerated shortening of telomeres. Consequently, obese persons are more likely to have shorter telomeres, but the association between body mass index (BMI) and leukocyte telomere length (TL) might differ across the life span and between ethnicities and sexes.

Objective: A collaborative cross-sectional meta-analysis of observational studies was conducted to investigate the associations between BMI and TL across the life span.

Design: Eighty-seven distinct study samples were included in the meta-analysis capturing data from 146,114 individuals. Study-specific age- and sex-adjusted regression coefficients were combined by using a random-effects model in which absolute [base pairs (bp)] and relative telomere to single-copy gene ratio (T/S ratio) TLs were regressed against BMI. Stratified analysis was performed by 3 age categories ("young": 18-60 y; "middle": 61-75 y; and "old": >75 y), sex, and ethnicity.

Results: Each unit increase in BMI corresponded to a -3.99 bp (95% CI: -5.17, -2.81 bp) difference in TL in the total pooled sample; among young adults, each unit increase in BMI corresponded to a -7.67 bp (95% CI: -10.03, -5.31 bp) difference. Each unit increase in BMI corresponded to a -1.58 × 10(-3) unit T/S ratio (0.16% decrease; 95% CI: -2.14 × 10(-3), -1.01 × 10(-3)) difference in age- and sex-adjusted relative TL in the total pooled sample; among young adults, each unit increase in BMI corresponded to a -2.58 × 10(-3) unit T/S ratio (0.26% decrease; 95% CI: -3.92 × 10(-3), -1.25 × 10(-3)). The associations were predominantly for the white pooled population. No sex differences were observed.

Conclusions: A higher BMI is associated with shorter telomeres, especially in younger individuals. The presently observed difference is not negligible. Meta-analyses of longitudinal studies evaluating change in body weight alongside change in TL are warranted.
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http://dx.doi.org/10.1093/ajcn/nqy107DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454526PMC
September 2018

Different Growth Patterns Persist at 24 Months of Age in Formula-Fed Infants Randomized to Consume a Meat- or Dairy-Based Complementary Diet from 5 to 12 Months of Age.

J Pediatr 2019 03 6;206:78-82. Epub 2018 Nov 6.

Section of Nutrition, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO.

Objective: To test the long-term effect on growth status at 24 months of age in formula-fed infants who were randomized to consume a meat- or dairy-based complementary diet from 5 to 12 months of age.

Study Design: Observational assessments, including anthropometric, dietary, and blood biomarkers, were conducted at 24 months of age, 1 year after the intervention ended.

Results: The retention rate at 24 months of age was 84% for the meat group and 81% for the dairy group. Mean (±SD) protein intakes at 24 months of age were 4.1 ± 1.2 and 4.0 ± 1.1 g/kmeat (n = 27) and dairy (n = 26) groups, respectively, and comparable with the estimates of US population intake. At 24 months of age, weight-for-age z score did not differ significantly between groups and was similar to that at 12 months. Length-for-age z score remained significantly higher in the meat group compared with the dairy group, and the average length was 1.9 cm greater in the meat group. Weight-for-length z score also did not differ significantly between groups. Insulin-like growth factor 1 significantly increased from 12 to 24 months of age in both groups, but insulin-like growth factor-binding protein 3 and blood urea nitrogen did not change significantly from 12 to 24 months of age and were comparable between groups.

Conclusions: The protein source-induced distinctive growth patterns observed during infancy persisted at 24 months of age, suggesting a potential long-term impact of early protein quality on growth trajectories in formula-fed infants.

Trial Registration: ClinicalTrials.gov: NCT02142647.
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http://dx.doi.org/10.1016/j.jpeds.2018.10.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389371PMC
March 2019

ProxECAT: Proxy External Controls Association Test. A new case-control gene region association test using allele frequencies from public controls.

PLoS Genet 2018 10 16;14(10):e1007591. Epub 2018 Oct 16.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America.

A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis.
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http://dx.doi.org/10.1371/journal.pgen.1007591DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191077PMC
October 2018

A meat- or dairy-based complementary diet leads to distinct growth patterns in formula-fed infants: a randomized controlled trial.

Am J Clin Nutr 2018 05;107(5):734-742

Section of Nutrition, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO.

Background: Protein intake from cow milk-based infant formula has been associated with rapid weight gain and increased adiposity, but the effect of protein from complementary foods has not been prospectively evaluated, and the effect of protein from sources other than formula during complementary feeding is not clear.

Objective: The aim of this study was to directly compare the effect of protein from 2 common complementary food sources, meat and dairy, on infant growth and weight trajectory.

Design: Healthy term, formula-fed infants were recruited from the metro Denver area, matched by sex and race/ethnicity and randomly assigned to a meat or a dairy complementary food group from 5 to 12 mo of age. Total protein intake during this 7-mo intervention was ∼3 g ⋅ kg-1 ⋅ d-1 for both groups. Intakes of infant formula, cereal, fruit, and vegetables were ad libitum. Caregivers also completed 3-d diet records at 5, 10, and 12 mo of age. Anthropometric measures were obtained during monthly home visits, and blood samples were collected at 5 and 12 mo of age.

Results: Sixty-four infants completed the intervention (meat: n = 32; dairy: n = 32). The average total protein intake (mean ± SD) increased from 2.01 ± 0.06 g ⋅ kg-1 ⋅ d-1 at 5 mo to 3.35 ±0.12 g ⋅ kg-1 ⋅ d-1 at 12 mo and did not differ between groups. Over time, weight and weight-for-age z score increased by 0.48 ± 0.07. However, there was a significant group-by-time interaction for both length-for-age z score (LAZ) and weight-for-length z score (WLZ). Post hoc analysis showed that LAZ increased in the meat group (+0.33 ± 0.09; P = 0.001 over time) and decreased in the dairy group (-0.30 ± 0.10; P = 0.0002 over time); WLZ significantly increased in the dairy group (0.76 ± 0.21; P = 0.000002 over time) compared with the meat group (0.30 ± 0.17; P = 0.55 over time). Insulin-like growth factor I and insulin-like growth factor-binding protein 3 both increased over time without group differences.

Conclusions: Protein source may have an important role in regulating growth. In these formula-fed older infants, meat- and dairy-based complementary foods led to distinct growth patterns, especially for length. This trial was registered at www.clinicaltrials.gov as NCT02142647.
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http://dx.doi.org/10.1093/ajcn/nqy038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6128676PMC
May 2018

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 05;50(5):766-767

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0082-3DOI Listing
May 2018

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 01 22;50(1):26-41. Epub 2017 Dec 22.

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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http://dx.doi.org/10.1038/s41588-017-0011-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945951PMC
January 2018

Iron in Micronutrient Powder Promotes an Unfavorable Gut Microbiota in Kenyan Infants.

Nutrients 2017 Jul 19;9(7). Epub 2017 Jul 19.

Section of Nutrition, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045, USA.

Iron supplementation may have adverse health effects in infants, probably through manipulation of the gut microbiome. Previous research in low-resource settings have focused primarily on anemic infants. This was a double blind, randomized, controlled trial of home fortification comparing multiple micronutrient powder (MNP) with and without iron. Six-month-old, non- or mildly anemic, predominantly-breastfed Kenyan infants in a rural malaria-endemic area were randomized to consume: (1) MNP containing 12.5 mg iron (MNP+Fe, = 13); (2) MNP containing no iron (MNP-Fe, = 13); or (3) Placebo (CONTROL, = 7), from 6-9 months of age. Fecal microbiota were profiled by high-throughput bacterial 16S rRNA gene sequencing. Markers of inflammation in serum and stool samples were also measured. At baseline, the most abundant phylum was Proteobacteria (37.6% of rRNA sequences). The proteobacterial genus was the most abundant genus across all phyla (30.1% of sequences). At the end of the intervention, the relative abundance of significantly decreased in MNP-Fe (-16.05 ± 6.9%, = 0.05) and CONTROL (-19.75 ± 4.5%, = 0.01), but not in the MNP+Fe group (-6.23 ± 9%, = 0.41). The second most abundant genus at baseline was (17.3%), the relative abundance of which significantly decreased in MNP+Fe (-6.38 ± 2.5%, = 0.02) and CONTROL (-8.05 ± 1.46%, = 0.01), but not in MNP-Fe (-4.27 ± 5%, = 0.4445). increased in MNP-Fe only (1.9 ± 0.5%, = 0.02). No significant differences were observed in inflammation markers, except for IL-8, which decreased in CONTROL. MNP fortification over three months in non- or mildly anemic Kenyan infants can potentially alter the gut microbiome. Consistent with previous research, addition of iron to the MNP may adversely affect the colonization of potential beneficial microbes and attenuate the decrease of potential pathogens.
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http://dx.doi.org/10.3390/nu9070776DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537890PMC
July 2017

Rare Variant Analysis of Human and Rodent Obesity Genes in Individuals with Severe Childhood Obesity.

Sci Rep 2017 06 29;7(1):4394. Epub 2017 Jun 29.

University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK.

Obesity is a genetically heterogeneous disorder. Using targeted and whole-exome sequencing, we studied 32 human and 87 rodent obesity genes in 2,548 severely obese children and 1,117 controls. We identified 52 variants contributing to obesity in 2% of cases including multiple novel variants in GNAS, which were sometimes found with accelerated growth rather than short stature as described previously. Nominally significant associations were found for rare functional variants in BBS1, BBS9, GNAS, MKKS, CLOCK and ANGPTL6. The p.S284X variant in ANGPTL6 drives the association signal (rs201622589, MAF~0.1%, odds ratio = 10.13, p-value = 0.042) and results in complete loss of secretion in cells. Further analysis including additional case-control studies and population controls (N = 260,642) did not support association of this variant with obesity (odds ratio = 2.34, p-value = 2.59 × 10), highlighting the challenges of testing rare variant associations and the need for very large sample sizes. Further validation in cohorts with severe obesity and engineering the variants in model organisms will be needed to explore whether human variants in ANGPTL6 and other genes that lead to obesity when deleted in mice, do contribute to obesity. Such studies may yield druggable targets for weight loss therapies.
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http://dx.doi.org/10.1038/s41598-017-03054-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5491520PMC
June 2017

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits.

Am J Hum Genet 2017 Jun 25;100(6):865-884. Epub 2017 May 25.

Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Cardiology, Ealing Hospital NHS Trust, Middlesex UB1 3EU, UK.

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.
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http://dx.doi.org/10.1016/j.ajhg.2017.04.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473732PMC
June 2017

Gene-gene Interaction Analyses for Atrial Fibrillation.

Sci Rep 2016 11 8;6:35371. Epub 2016 Nov 8.

Department of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.

Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in an independent cohort for replication, which included more than 2,363 AF cases and 114,746 AF-free referents. One interaction, between rs7164883 at the HCN4 locus and rs4980345 at the SLC28A1 locus, was found to be significantly associated with AF in the discovery cohorts (interaction OR = 1.44, 95% CI: 1.27-1.65, P = 4.3 × 10). Eight additional gene-gene interactions were also marginally significant (P < 5 × 10). However, none of the top interactions were replicated. In summary, we did not find significant interactions that were associated with AF susceptibility. Future increases in sample size and denser genotyping might facilitate the identification of gene-gene interactions associated with AF.
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http://dx.doi.org/10.1038/srep35371DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5099695PMC
November 2016

Whole-exome sequencing in an isolated population from the Dalmatian island of Vis.

Eur J Hum Genet 2016 10 6;24(10):1479-87. Epub 2016 Apr 6.

Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.

We have whole-exome sequenced 176 individuals from the isolated population of the island of Vis in Croatia in order to describe exonic variation architecture. We found 290 577 single nucleotide variants (SNVs), 65% of which are singletons, low frequency or rare variants. A total of 25 430 (9%) SNVs are novel, previously not catalogued in NHLBI GO Exome Sequencing Project, UK10K-Generation Scotland, 1000Genomes Project, ExAC or NCBI Reference Assembly dbSNP. The majority of these variants (76%) are singletons. Comparable to data obtained from UK10K-Generation Scotland that were sequenced and analysed using the same protocols, we detected an enrichment of potentially damaging variants (non-synonymous and loss-of-function) in the low frequency and common variant categories. On average 115 (range 93-140) genotypes with loss-of-function variants, 23 (15-34) of which were homozygous, were identified per person. The landscape of loss-of-function variants across an exome revealed that variants mainly accumulated in genes on the xenobiotic-related pathways, of which majority coded for enzymes. The frequency of loss-of-function variants was additionally increased in Vis runs of homozygosity regions where variants mainly affected signalling pathways. This work confirms the isolate status of Vis population by means of whole-exome sequence and reveals the pattern of loss-of-function mutations, which resembles the trails of adaptive evolution that were found in other species. By cataloguing the exomic variants and describing the allelic structure of the Vis population, this study will serve as a valuable resource for future genetic studies of human diseases, population genetics and evolution in this population.
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http://dx.doi.org/10.1038/ejhg.2016.23DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4950961PMC
October 2016

Progress in methods for rare variant association.

BMC Genet 2016 Feb 3;17 Suppl 2. Epub 2016 Feb 3.

Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, 80217-3364, USA.

Empirical studies and evolutionary theory support a role for rare variants in the etiology of complex traits. Given this motivation and increasing affordability of whole-exome and whole-genome sequencing, methods for rare variant association have been an active area of research for the past decade. Here, we provide a survey of the current literature and developments from the Genetics Analysis Workshop 19 (GAW19) Collapsing Rare Variants working group. In particular, we present the generalized linear regression framework and associated score statistic for the 2 major types of methods: burden and variance components methods. We further show that by simply modifying weights within these frameworks we arrive at many of the popular existing methods, for example, the cohort allelic sums test and sequence kernel association test. Meta-analysis techniques are also described. Next, we describe the 6 contributions from the GAW19 Collapsing Rare Variants working group. These included development of new methods, such as a retrospective likelihood for family data, a method using genomic structure to compare cases and controls, a haplotype-based meta-analysis, and a permutation-based method for combining different statistical tests. In addition, one contribution compared a mega-analysis of family-based and population-based data to meta-analysis. Finally, the power of existing family-based methods for binary traits was compared. We conclude with suggestions for open research questions.
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http://dx.doi.org/10.1186/s12863-015-0316-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895384PMC
February 2016

The UK10K project identifies rare variants in health and disease.

Nature 2015 Oct 14;526(7571):82-90. Epub 2015 Sep 14.

The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.
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http://dx.doi.org/10.1038/nature14962DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4773891PMC
October 2015

Genetic associations with expression for genes implicated in GWAS studies for atherosclerotic cardiovascular disease and blood phenotypes.

Hum Mol Genet 2014 Feb 20;23(3):782-95. Epub 2013 Sep 20.

Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA.

Genome-wide association studies (GWAS) have uncovered many genetic associations for cardiovascular disease (CVD). However, data are limited regarding causal genetic variants within implicated loci. We sought to identify regulatory variants (cis- and trans-eQTLs) affecting expression levels of 93 genes selected by their proximity to SNPs with significant associations in prior GWAS for CVD traits. Expression levels were measured by qRT-PCR in leukocytes from 1846 Framingham Heart Study participants. An additive genetic model was applied to 2.5 million imputed SNPs for each gene. Approximately 45% of genes (N = 38) harbored at least one cis-eSNP after a regional multiple-test adjustment. Applying a more rigorous significance threshold (P < 5 × 10(-8)), we found the expression level of 10 genes was significantly associated with more than one cis-eSNP. The top cis-eSNPs for 7 of these 10 genes exhibited moderate-to-strong association with ≥ 1 CVD clinical phenotypes. Several eSNPs or proxy SNPs (r(2) = 1) were replicated by other eQTL studies. After adjusting for the lead GWAS SNPs for the 10 genes, expression variances explained by top cis-eSNPs were attenuated markedly for LPL, FADS2 and C6orf184, suggesting a shared genetic basis for the GWAS and expression trait. A significant association between cis-eSNPs, gene expression and lipid levels was discovered for LPL and C6orf184. In conclusion, strong cis-acting variants are localized within nearly half of the GWAS loci studied, with particularly strong evidence for a regulatory role of the top GWAS SNP for expression of LPL, FADS2 and C6orf184.
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http://dx.doi.org/10.1093/hmg/ddt461DOI Listing
February 2014

Correction for multiple testing in a gene region.

Eur J Hum Genet 2014 Mar 10;22(3):414-8. Epub 2013 Jul 10.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.

Several methods to correct for multiple testing within a gene region have been proposed. These methods are useful for candidate gene studies, and to fine map gene-regions from GWAs. The Bonferroni correction and permutation are common adjustments, but are overly conservative and computationally intensive, respectively. Other options include calculating the effective number of independent single-nucleotide polymorphisms (SNPs) or using theoretical approximations. Here, we compare a theoretical approximation based on extreme tail theory with four methods for calculating the effective number of independent SNPs. We evaluate the type-I error rates of these methods using single SNP association tests over 10 gene regions simulated using 1000 Genomes data. Overall, we find that the effective number of independent SNP method by Gao et al, as well as extreme tail theory produce type-I error rates at the or close to the chosen significance level. The type-I error rates for the other effective number of independent SNP methods vary by gene region characteristics. We find Gao et al and extreme tail theory to be efficient alternatives to more computationally intensive approaches to control for multiple testing in gene regions.
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http://dx.doi.org/10.1038/ejhg.2013.144DOI Listing
March 2014

Assessment of cortical and striatal involvement in 523 Huntington disease brains.

Neurology 2012 Oct 3;79(16):1708-15. Epub 2012 Oct 3.

Department of Neurology, Boston University School of Medicine, Boston, MA, USA.

Objective: To evaluate the relationship of striatal involvement in Huntington disease (HD) to involvement in other brain regions, CAG repeat size, onset age, and other factors.

Methods: We examined patterns of neuropathologic involvement in 664 HD brains submitted to the Harvard Brain Tissue Resource Center. Brains with concomitant Alzheimer or Parkinson changes (n = 82), more than 20% missing data (n = 46), incomplete sample submission (n = 12), or CAG repeat less than 36 (n = 1) were excluded, leaving 523 cases. Standardized ratings from 0 (absent) to 4 (severe) of gross and microscopic involvement were performed for 50 regions. Cluster analysis reduced the data to 2 main measures of involvement: striatal and cortical.

Results: The clusters were correlated with each other (r = 0.42) and with disease duration (striatal: r = 0.35; cortical: r = 0.31). The striatal cluster was correlated with HD repeat size (r = 0.50). The cortical cluster showed a stronger correlation with decreased brain weight (r = -0.52) than the striatal cluster (r = -0.33). The striatal cluster was correlated with younger death age (r = -0.31) and onset age (r = -0.46) while the cortical cluster was not (r = 0.09, r = -0.04, respectively).

Conclusions: The 2 brain clusters had different relationships to the HD CAG repeat size, onset age, and brain weight, suggesting that neuropathologic involvement does not proceed in a strictly coupled fashion. The pattern and extent of involvement varies substantially from one brain to the next. These results suggest that regional involvement in HD brain is modified by factors which, if identified, may lend insight into novel routes to therapeutics.
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http://dx.doi.org/10.1212/WNL.0b013e31826e9a5dDOI Listing
October 2012

A comparison of gene region simulation methods.

PLoS One 2012 18;7(7):e40925. Epub 2012 Jul 18.

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America.

Background: Accurately modeling LD in simulations is essential to correctly evaluate new and existing association methods. At present, there has been minimal research comparing the quality of existing gene region simulation methods to produce LD structures similar to an existing gene region. Here we compare the ability of three approaches to accurately simulate the LD within a gene region: HapSim (2005), Hapgen (2009), and a minor extension to simple haplotype resampling.

Methodology/principal Findings: In order to observe the variation and bias for each method, we compare the simulated pairwise LD measures and minor allele frequencies to the original HapMap data in an extensive simulation study. When possible, we also evaluate the effects of changing parameters. HapSim produces samples of haplotypes with lower LD, on average, compared to the original haplotype set while both our resampling method and Hapgen do not introduce this bias. The variation introduced across the replicates by our resampling method is quite small and may not provide enough sampling variability to make a generalizable simulation study.

Conclusion: We recommend using Hapgen to simulate replicate haplotypes from a gene region. Hapgen produces moderate sampling variation between the replicates while retaining the overall unique LD structure of the gene region.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0040925PLOS
March 2013
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