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Hujoel MLA, Handsaker RE, Sherman MA, Kamitaki N, Barton AR, Mukamel RE, Terao C, McCarroll SA, Loh PR. Protein-altering variants at copy number-variable regions influence diverse human phenotypes. Nat Genet 2024; 56:569-578. [PMID: 38548989 PMCID: PMC11018521 DOI: 10.1038/s41588-024-01684-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 02/08/2024] [Indexed: 04/09/2024]
Abstract
Copy number variants (CNVs) are among the largest genetic variants, yet CNVs have not been effectively ascertained in most genetic association studies. Here we ascertained protein-altering CNVs from UK Biobank whole-exome sequencing data (n = 468,570) using haplotype-informed methods capable of detecting subexonic CNVs and variation within segmental duplications. Incorporating CNVs into analyses of rare variants predicted to cause gene loss of function (LOF) identified 100 associations of predicted LOF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 conferred one of the strongest protective effects of gene LOF on hypertension risk (odds ratio = 0.86 (0.82-0.90)). Protein-coding variation in rapidly evolving gene families within segmental duplications-previously invisible to most analysis methods-generated some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.
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Affiliation(s)
- Margaux L A Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Robert E Handsaker
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Serinus Biosciences Inc., New York, NY, USA
| | - Nolan Kamitaki
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Hujoel IA, Hujoel MLA. The Rising Incidence and Poor Outcomes of Enteropathy-Associated T-Cell Lymphoma. Am J Gastroenterol 2024:00000434-990000000-00983. [PMID: 38235779 DOI: 10.14309/ajg.0000000000002666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 01/15/2024] [Indexed: 01/19/2024]
Abstract
INTRODUCTION Enteropathy-associated T-cell lymphoma (EATL) is associated with celiac disease. With the rising prevalence of celiac disease, we hypothesized that the prevalence of EATL is also increasing. METHODS We used the Surveillance, Epidemiology, and End Results database, which is a population-based US cancer surveillance program. We used the ICD-0-3 code 9717/3 to identify patients with EATL diagnosed between 2000 and 2020. Incidence rates were calculated using the SEER*Stat software, and annual percent change was calculated using the Joinpoint software. Log-rank tests were used to evaluate for significant difference in survival curves between groups. A Cox proportional hazards regression model was used for continuous variables and quantifying association strength of predictors. RESULTS A total of 463 cases of EATL were identified (273 male, 190 female) with a median age of 65 (range 23-90+) years. Most of the cases were at an advanced stage at diagnosis and were treated with a combination of surgery and chemotherapy. The median survival time was 6 months. The 2000-2020 age-adjusted incidence rate per 100,000 people was 0.014, and the incidence increased between 2000 and 2020, with an annual percent change of 2.58 ( P < 0.05). Increased age at diagnosis and lack of treatment had significant impacts on survival while sex, year of diagnosis, race, and time between diagnosis and treatment had no significant impact on survival. DISCUSSION There was a significant increase in the incidence of EATL in the United States between 2000 and 2020. Survival in this cancer remains poor and unchanged over the past 2 decades.
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Affiliation(s)
- Isabel A Hujoel
- Division of Gastroenterology, University of Washington, Seattle, Washington, USA
| | - Margaux L A Hujoel
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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Hujoel IA, Hujoel MLA, Choung RS, Murray JA. Symptom Outcomes of Celiac Disease in Those on a Gluten-free Diet. J Clin Gastroenterol 2023:00004836-990000000-00236. [PMID: 38019078 DOI: 10.1097/mcg.0000000000001946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 10/20/2023] [Indexed: 11/30/2023]
Abstract
GOALS We aimed to evaluate symptom outcomes in those on a gluten-free diet during the 5 years after diagnosis. BACKGROUND Celiac disease is common; however, little is known about long-term symptom outcomes. STUDY We performed a retrospective chart review on individuals with celiac disease followed at a tertiary referral center between 2012 and 2018. To minimize bias, strict inclusion/exclusion criteria were utilized. Only those with definitive biopsy-proven celiac disease, on a gluten-free diet, and with systematic follow-up were included. The standardized care at this center reduced the risk that decisions on testing and follow-up visits were determined by symptom status. Summary statistics were computed and generalized linear models with a logit link were used to associate the proportion of symptomatic visits with various covariates using R statistical programming. RESULTS Of the 1023 records reviewed, 212 met inclusion/exclusion criteria; 146 (69%) were female and the mean age at diagnosis was 43 (range: 11 to 84 y old). During follow-up, over 50% remained symptomatic, with many having the same symptoms that prompted the diagnosis. The only predictors for remaining symptomatic were female sex and younger age at diagnosis. Abnormal serology during follow-up and small bowel normalization were not predictive. CONCLUSIONS In individuals with definitive celiac disease with systematic long-term follow-up in a Celiac Clinic, roughly half remained symptomatic despite a gluten-free diet. Many suffer from the same symptoms that prompted the diagnosis of celiac disease. Small bowel healing and abnormal serology in follow-up were not predictive of remaining symptomatic. These findings stress the importance of long-term care in celiac disease.
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Affiliation(s)
- Isabel A Hujoel
- Division of Gastroenterology, Department of Internal Medicine University of Washington, Seattle, WA
| | - Margaux L A Hujoel
- Division of Genetics, Department of Medicine Brigham and Women's Hospital and Harvard Medical School, Boston
- Program in Medical and Population Genetics Broad Institute of MIT and Harvard, Cambridge, MA
| | - Rok Seon Choung
- Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Joseph A Murray
- Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
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Mukamel RE, Handsaker RE, Sherman MA, Barton AR, Hujoel MLA, McCarroll SA, Loh PR. Repeat polymorphisms underlie top genetic risk loci for glaucoma and colorectal cancer. Cell 2023; 186:3659-3673.e23. [PMID: 37527660 PMCID: PMC10528368 DOI: 10.1016/j.cell.2023.07.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 04/07/2023] [Accepted: 07/03/2023] [Indexed: 08/03/2023]
Abstract
Many regions in the human genome vary in length among individuals due to variable numbers of tandem repeats (VNTRs). To assess the phenotypic impact of VNTRs genome-wide, we applied a statistical imputation approach to estimate the lengths of 9,561 autosomal VNTR loci in 418,136 unrelated UK Biobank participants and 838 GTEx participants. Association and statistical fine-mapping analyses identified 58 VNTRs that appeared to influence a complex trait in UK Biobank, 18 of which also appeared to modulate expression or splicing of a nearby gene. Non-coding VNTRs at TMCO1 and EIF3H appeared to generate the largest known contributions of common human genetic variation to risk of glaucoma and colorectal cancer, respectively. Each of these two VNTRs associated with a >2-fold range of risk across individuals. These results reveal a substantial and previously unappreciated role of non-coding VNTRs in human health and gene regulation.
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Affiliation(s)
- Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Robert E Handsaker
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Genetics, Harvard Medical School, Boston, MA, USA.
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Bioinformatics and Integrative Genomics Program, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Margaux L A Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Genetics, Harvard Medical School, Boston, MA, USA.
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Hujoel MLA, Sherman MA, Barton AR, Mukamel RE, Sankaran VG, Terao C, Loh PR. Influences of rare copy-number variation on human complex traits. Cell 2022; 185:4233-4248.e27. [PMID: 36306736 PMCID: PMC9800003 DOI: 10.1016/j.cell.2022.09.028] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 07/22/2022] [Accepted: 09/19/2022] [Indexed: 11/06/2022]
Abstract
The human genome contains hundreds of thousands of regions harboring copy-number variants (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs have been ascertainable from SNP-array data generated by large biobanks. We developed a computational approach leveraging haplotype sharing in biobank cohorts to more sensitively detect CNVs. Applied to UK Biobank, this approach accounted for approximately half of all rare gene inactivation events produced by genomic structural variation. This CNV call set enabled a detailed analysis of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (p < 5 × 10-8) likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling insights into dosage sensitivity of these genes and uncovering several gene-trait relationships. These results demonstrate the ability of haplotype-informed analysis to provide insights into the genetic basis of human complex traits.
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Affiliation(s)
- Margaux L A Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Bioinformatics and Integrative Genomics Program, Harvard Medical School, Boston, MA, USA
| | - Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vijay G Sankaran
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan; Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Barton AR, Hujoel MLA, Mukamel RE, Sherman MA, Loh PR. A spectrum of recessiveness among Mendelian disease variants in UK Biobank. Am J Hum Genet 2022; 109:1298-1307. [PMID: 35649421 PMCID: PMC9300759 DOI: 10.1016/j.ajhg.2022.05.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 05/12/2022] [Indexed: 01/09/2023] Open
Abstract
Recent work has found increasing evidence of mitigated, incompletely penetrant phenotypes in heterozygous carriers of recessive Mendelian disease variants. We leveraged whole-exome imputation within the full UK Biobank cohort (n ∼ 500K) to extend such analyses to 3,475 rare variants curated from ClinVar and OMIM. Testing these variants for association with 58 quantitative traits yielded 102 significant associations involving variants previously implicated in 34 different diseases. Notable examples included a POR missense variant implicated in Antley-Bixler syndrome that associated with a 1.76 (SE 0.27) cm increase in height and an ABCA3 missense variant implicated in interstitial lung disease that associated with reduced FEV1/FVC ratio. Association analyses with 1,134 disease traits yielded five additional variant-disease associations. We also observed contrasting levels of recessiveness between two more-common, classical Mendelian diseases. Carriers of cystic fibrosis variants exhibited increased risk of several mitigated disease phenotypes, whereas carriers of spinal muscular atrophy alleles showed no evidence of altered phenotypes. Incomplete penetrance of cystic fibrosis carrier phenotypes did not appear to be mediated by common allelic variation on the functional haplotype. Our results show that many disease-associated recessive variants can produce mitigated phenotypes in heterozygous carriers and motivate further work exploring penetrance mechanisms.
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Affiliation(s)
- Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Bioinformatics and Integrative Genomics Program, Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
| | - Margaux L A Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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Hujoel PP, Hujoel MLA. Vitamin C and scar strength: analysis of a historical trial and implications for collagen-related pathologies. Am J Clin Nutr 2022; 115:8-17. [PMID: 34396385 DOI: 10.1093/ajcn/nqab262] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Accepted: 07/15/2021] [Indexed: 01/02/2023] Open
Abstract
A double-blind controlled trial initiated in 1944 has led to the common narrative that a 10-mg daily vitamin C intake is adequate to prevent and treat impaired wound healing, and by inference, other collagen-related diseases such as heart disease or stroke. The WHO relies on this narrative to set the recommended nutrient intake for vitamin C. This narrative, however, is based on what is known as the eyeball method of data assessment. The 1944 trial published individual participant data on scar strength providing an opportunity to statistically probe the validity of the 10-mg narrative, something which has not yet been done. The findings show that a vitamin C intake that averages to 10 mg/d over a mean follow-up of 11.5 mo was associated with a 42% weakened scar strength when compared with 80 mg vitamin C intake/d (P < 0.001). The observed dose-response curve between scar strength and vitamin C intake suggests that the daily vitamin C intake needed to prevent collagen-related pathologies is in the range recommended by the National Academy of Medicine and the European Food Safety Authority (75 to 110 mg/d), not the WHO recommendation (45 mg/d). The findings also show that a vitamin C intake that averages to 65 mg/d over a mean follow-up of 6.5 mo failed to restore the normal wound-healing capacity of vitamin C-depleted tissues; such tissues had a 49% weaker scar strength when compared with nondepleted tissues (P < 0.05). Thus, average daily vitamin C intakes ∼50% higher than the WHO recommends may fail to treat existing collagen-related pathologies. It is concluded that the prior lack of statistical analyses of a landmark trial may have led to a misleading narrative on the vitamin C needs for the prevention and treatment of collagen-related pathologies.
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Affiliation(s)
- Philippe P Hujoel
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.,Department of Oral Health Sciences, School of Dentistry, University of Washington, Seattle, WA, USA
| | - Margaux L A Hujoel
- Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Hujoel IA, Hujoel MLA. The Role of Copper and Zinc in Irritable Bowel Syndrome: A Mendelian Randomization Study. Am J Epidemiol 2022; 191:85-92. [PMID: 34132328 DOI: 10.1093/aje/kwab180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 05/30/2021] [Accepted: 06/11/2021] [Indexed: 11/14/2022] Open
Abstract
Irritable bowel syndrome (IBS) has been associated with copper and zinc imbalance and a zinc-deficient diet. Mendelian randomization was used in this study to evaluate if genetically determined copper and zinc levels play a causal role in the development of IBS. Three single-nucleotide polymorphisms (SNPs; rs1175550, rs2769264, and rs2769270) associated with erythrocyte copper levels, and 3 SNPs associated with erythrocyte zinc levels (rs11638477, rs1532423, and rs2120019) in the Australian Twin Study (1993-1996 and 2001-2005) were used as instrumental variables for levels of these metals. The association of these SNPs with IBS was tested using summary statistics computed from data on 340,331 individuals from the UK Biobank, 5,548 of whom had IBS (2006-2010). Genetically predicted high serum copper levels were associated with a lower risk of IBS (odds ratio = 0.89; 95% confidence interval: 0.80, 0.98). Genetically predicted, high serum zinc levels were nonsignificantly associated with a higher risk of IBS (odds ratio = 1.06; 95% confidence interval: 0.95, 1.18). Sensitivity analysis did not suggest the presence of pleiotropy. These results suggest that high erythrocyte copper levels may be protective against IBS development. Targeting higher levels, therefore, may provide an avenue to reduce the likelihood of IBS development in high-risk individuals.
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Hujoel IA, Jansson-Knodell CL, Hujoel PP, Hujoel MLA, Choung RS, Murray JA, Rubio-Tapia A. Estimating the Impact of Verification Bias on Celiac Disease Testing. J Clin Gastroenterol 2021; 55:327-334. [PMID: 32433257 PMCID: PMC7674196 DOI: 10.1097/mcg.0000000000001361] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/06/2020] [Indexed: 01/19/2023]
Abstract
GOAL The goal of this study was to estimate the impact of verification bias on the diagnostic accuracy of immunoglobulin A tissue transglutaminase (IgA tTG) in detecting celiac disease as reported by an authoritative meta-analysis, the 2016 Comparative Effectiveness Review (CER). BACKGROUND Verification bias is introduced to diagnostic accuracy studies when screening test results impact the decision to verify disease status. MATERIALS AND METHODS We adjusted the sensitivity and specificity of IgA tTG reported by the 2016 CER with the proportion of IgA tTG positive and negative individuals who are referred for confirmatory small bowel biopsy. We performed a systematic review from January 1, 2007, to July 19, 2017, to determine these referral rates. RESULTS The systematic review identified 793 articles of which 9 met inclusion criteria (n=36,477). Overall, 3.6% [95% confidence interval (CI): 1.1%-10.9%] of IgA tTG negative and 79.2.2% (95% CI: 65.0%-88.7%) of IgA tTG positive individuals were referred for biopsy. Adjusting for these referral rates the 2016 CER reported sensitivity of IgA tTG dropped from 92.6% (95% CI: 90.2%-94.5%) to 57.1% (95% CI: 35.4%-76.4%) and the specificity increased from 97.6% (95% CI: 96.3%-98.5%) to 99.6% (95% CI: 98.4%-99.9%). CONCLUSIONS The CER may have largely overestimated the sensitivity of IgA tTG due to a failure to account for verification bias. These findings suggest caution in the interpretation of a negative IgA tTG to rule out celiac disease in clinical practice. More broadly, they highlight the impact of verification bias on diagnostic accuracy estimates and suggest that studies at risk for this bias be excluded from systematic reviews.
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Affiliation(s)
- Isabel A. Hujoel
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905
| | | | - Philippe P. Hujoel
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195
| | - Margaux L. A. Hujoel
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02215
| | - Rok Seon Choung
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905
| | - Joseph A. Murray
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905
| | - Alberto Rubio-Tapia
- Department of Gastroenterology and Hepatology, Cleveland Clinic, Cleveland, OH, 44103
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Hujoel PP, Kato T, Hujoel IA, Hujoel MLA. Bleeding tendency and ascorbic acid requirements: systematic review and meta-analysis of clinical trials. Nutr Rev 2021; 79:964-975. [PMID: 33517432 DOI: 10.1093/nutrit/nuaa115] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
CONTEXT The World Health Organization set the recommended daily vitamin C intake, henceforth referred to as ascorbic acid (AA), on the basis of scurvy prevention. Double-blind AA depletion-repletion studies suggest that this recommended AA dose may be too low to prevent microvascular fragility. OBJECTIVES (1) To conduct a systematic review and meta-analysis of controlled clinical trials on whether AA supplementation leads to a reduced gingival bleeding tendency, a manifestation of microvascular fragility; and (2) to relate AA plasma levels to retinal hemorrhaging, another manifestation of microvascular fragility. DATA SOURCES Data were reviewed from 15 trials conducted in 6 countries with 1140 predominantly healthy participants with measures of gingival bleeding tendency, and from the National Health and Nutrition Examination Survey (NHANES) III of 8210 US residents with measures of retinal hemorrhaging. RESULTS In clinical trials, AA supplementation reduced gingival bleeding tendency when estimated baseline AA plasma levels were < 28 μmol/L (standardized mean difference [SMD], -0.83; 95%CI, -1.16 to -0.49; P < 0.002). Supplementation with AA did not unequivocally reduce gingival bleeding tendency when baseline estimated AA plasma levels were >48 μmol/L or unknown (respective standardized mean differences: -0.23, 95%CI, -0.45 to -0.01, P < 0.05; and -0.56; 95%CI: -1.19 to 0.06, P < 0.08). In NHANES III, prevalence of both retinal hemorrhaging and gingival bleeding tendency increased when AA plasma levels were within the range that protects against scurvy (11-28 μmol/L; respective prevalence ratios adjusted for age and sex: 1.47; 95%CI: 1.22-1.77; and 1.64; 95%CI: 1.32-2.03; P < 0.001 for both). CONCLUSION Consistent evidence from controlled clinical trials indicates that setting human AA requirements based on scurvy prevention leads to AA plasma levels that may be too low to prevent an increased gingival bleeding tendency. Gingival bleeding tendency and retinal hemorrhaging coincide with low AA plasma levels and thus may be reflective of a systemic microvascular pathology that is reversible with an increased daily AA intake.
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Affiliation(s)
- Philippe P Hujoel
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA.,Department of Oral Health Sciences, School of Dentistry, University of Washington, Seattle, Washington, USA
| | - Tomotaka Kato
- Department of Oral Health Sciences, School of Dentistry, University of Washington, Seattle, Washington, USA
| | - Isabel A Hujoel
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Margaux L A Hujoel
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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Hujoel MLA, Parmigiani G, Braun D. Statistical approaches for meta-analysis of genetic mutation prevalence. Genet Epidemiol 2020; 45:154-170. [PMID: 33000511 PMCID: PMC10391692 DOI: 10.1002/gepi.22364] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 08/23/2020] [Accepted: 09/03/2020] [Indexed: 12/13/2022]
Abstract
Estimating the prevalence of rare germline genetic mutations in the general population is of interest as it can inform genetic counseling and risk management. Most studies that estimate the prevalence of mutations are performed in high-risk populations, and each study is designed with differing inclusion criteria, resulting in ascertained populations. Quantifying the effects of ascertainment is necessary to estimate the prevalence in the general population. This quantification is difficult as the inclusion criteria is often based on disease status and/or family history. Combining estimates from multiple studies through a meta-analysis is challenging due to the variety of study designs and ascertainment mechanisms as well as the complexity of quantifying the effect of these mechanisms. We provide guidelines on how to quantify the ascertainment mechanism for a wide range of settings and propose a general approach for conducting a meta-analysis in these complex settings by incorporating study-specific ascertainment mechanisms into a joint likelihood function. We implement the proposed likelihood-based approach using both frequentist and Bayesian methodologies. We evaluate these approaches in simulations and show that the methods are robust and produce unbiased estimates of the prevalence. An advantage of the Bayesian approach is that it can easily incorporate uncertainty in ascertainment probability values. We apply our methods to estimate the prevalence of PALB2 mutations in the United States by combining data from multiple studies and obtain a prevalence estimate of around 0.02%.
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Affiliation(s)
- Margaux L A Hujoel
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Division of Biostatistics, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Giovanni Parmigiani
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Division of Biostatistics, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Danielle Braun
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Division of Biostatistics, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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Affiliation(s)
- Margaux L. A. Hujoel
- Department of Biostatistics Harvard T.H. Chan School of Public Health Boston Massachusetts USA
- Division of Biostatistics Dana‐Farber Cancer Institute Boston Massachusetts USA
| | - Giovanni Parmigiani
- Department of Biostatistics Harvard T.H. Chan School of Public Health Boston Massachusetts USA
- Division of Biostatistics Dana‐Farber Cancer Institute Boston Massachusetts USA
| | - Danielle Braun
- Department of Biostatistics Harvard T.H. Chan School of Public Health Boston Massachusetts USA
- Division of Biostatistics Dana‐Farber Cancer Institute Boston Massachusetts USA
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13
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Hujoel MLA, Gazal S, Loh PR, Patterson N, Price AL. Liability threshold modeling of case-control status and family history of disease increases association power. Nat Genet 2020; 52:541-547. [PMID: 32313248 PMCID: PMC7210076 DOI: 10.1038/s41588-020-0613-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Accepted: 03/12/2020] [Indexed: 12/22/2022]
Abstract
Family history of disease can provide valuable information in case-control association studies, but it is currently unclear how to best combine case-control status and family history of disease. We developed an association method based on posterior mean genetic liabilities under a liability threshold model, conditional on case-control status and family history (LT-FH). Analyzing 12 diseases from the UK Biobank (average N = 350,000) we compared LT-FH to genome-wide association without using family history (GWAS) and a previous proxy-based method incorporating family history (GWAX). LT-FH was 63% (standard error (s.e.) 6%) more powerful than GWAS and 36% (s.e. 4%) more powerful than the trait-specific maximum of GWAS and GWAX, based on the number of independent genome-wide-significant loci across all diseases (for example, 690 loci for LT-FH versus 423 for GWAS); relative improvements were similar when applying BOLT-LMM to GWAS, GWAX and LT-FH phenotypes. Thus, LT-FH greatly increases association power when family history of disease is available.
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Affiliation(s)
- Margaux L A Hujoel
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Po-Ru Loh
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
| | | | - Alkes L Price
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Hormozdiari F, van de Geijn B, Nasser J, Weissbrod O, Gazal S, Ju CJT, Connor LO, Hujoel MLA, Engreitz J, Hormozdiari F, Price AL. Functional disease architectures reveal unique biological role of transposable elements. Nat Commun 2019; 10:4054. [PMID: 31492842 PMCID: PMC6731302 DOI: 10.1038/s41467-019-11957-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 08/08/2019] [Indexed: 12/19/2022] Open
Abstract
Transposable elements (TE) comprise roughly half of the human genome. Though initially derided as junk DNA, they have been widely hypothesized to contribute to the evolution of gene regulation. However, the contribution of TE to the genetic architecture of diseases remains unknown. Here, we analyze data from 41 independent diseases and complex traits to draw three conclusions. First, TE are uniquely informative for disease heritability. Despite overall depletion for heritability (54% of SNPs, 39 ± 2% of heritability), TE explain substantially more heritability than expected based on their depletion for known functional annotations. This implies that TE acquire function in ways that differ from known functional annotations. Second, older TE contribute more to disease heritability, consistent with acquiring biological function. Third, Short Interspersed Nuclear Elements (SINE) are far more enriched for blood traits than for other traits. Our results can help elucidate the biological roles that TE play in the genetic architecture of diseases.
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Affiliation(s)
- Farhad Hormozdiari
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA. .,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Bryce van de Geijn
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joseph Nasser
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Omer Weissbrod
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chelsea J-T Ju
- Department of Computer Science, University of California, Los Angeles, CA, 90095, USA
| | - Luke O' Connor
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.,Program in Bioinformatics and Integrative Genomics, Harvard Graduate School of Arts and Sciences, Boston, MA, USA
| | - Margaux L A Hujoel
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Jesse Engreitz
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Fereydoun Hormozdiari
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA, 95616, USA.,MIND Institute and UC-Davis Genome Center, Davis, CA, 95616, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA. .,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
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15
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Hujoel MLA, Gazal S, Hormozdiari F, van de Geijn B, Price AL. Disease Heritability Enrichment of Regulatory Elements Is Concentrated in Elements with Ancient Sequence Age and Conserved Function across Species. Am J Hum Genet 2019; 104:611-624. [PMID: 30905396 PMCID: PMC6451699 DOI: 10.1016/j.ajhg.2019.02.008] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 02/05/2019] [Indexed: 02/06/2023] Open
Abstract
Regulatory elements, e.g., enhancers and promoters, have been widely reported to be enriched for disease and complex trait heritability. We investigated how this enrichment varies with the age of the underlying genome sequence, the conservation of regulatory function across species, and the target gene of the regulatory element. We estimated heritability enrichment by applying stratified LD score regression to summary statistics from 41 independent diseases and complex traits (average N = 320K) and meta-analyzing results across traits. Enrichment of human putative enhancers and promoters was larger in elements with older sequence age, assessed via alignment with other species irrespective of conserved functionality: putative enhancer elements with ancient sequence age (older than the split between marsupial and placental mammals) were 8.8× enriched (versus 2.5× for all putative enhancers; p = 3e-14), and promoter elements with ancient sequence age were 13.5× enriched (versus 5.1× for all promoters; p = 5e-16). Enrichment of human putative enhancers and promoters was also larger in elements whose regulatory function was conserved across species, e.g., human putative enhancers that were enhancers in ≥5 of 9 other mammals were 4.6× enriched (p = 5e-12 versus all putative enhancers). Enrichment of human promoters was larger in promoters of loss-of-function intolerant genes: 12.0× enrichment (p = 8e-15 versus all promoters). The mean value of several measures of negative selection within these genomic annotations mirrored all of these findings. Notably, the annotations with these excess heritability enrichments were jointly significant conditional on each other and on our baseline-LD model, which includes a broad set of coding, conserved, regulatory, and LD-related annotations.
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Affiliation(s)
- Margaux L A Hujoel
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Division of Biostatistics, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Farhad Hormozdiari
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Bryce van de Geijn
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alkes L Price
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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