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Stefanucci L, Moslemi C, Tomé AR, Virtue S, Bidault G, Gleadall NS, Watson LPE, Kwa JE, Burden F, Farrow S, Chen J, Võsa U, Burling K, Walker L, Ord J, Barker P, Warner J, Frary A, Renhstrom K, Ashford SE, Piper J, Biggs G, Erber WN, Hoffman GJ, Schoenmakers N, Erikstrup C, Rieneck K, Dziegiel MH, Ullum H, Azzu V, Vacca M, Aparicio HJ, Hui Q, Cho K, Sun YV, Wilson PW, Bayraktar OA, Vidal-Puig A, Ostrowski SR, Astle WJ, Olsson ML, Storry JR, Pedersen OB, Ouwehand WH, Chatterjee K, Vuckovic D, Frontini M. SMIM1 absence is associated with reduced energy expenditure and excess weight. MED 2024:S2666-6340(24)00219-8. [PMID: 38906141 DOI: 10.1016/j.medj.2024.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 12/06/2023] [Accepted: 05/29/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Obesity rates have nearly tripled in the past 50 years, and by 2030 more than 1 billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are etiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments. METHODS We used a case-control approach to determine metabolic differences between individuals homozygous for a loss-of-function genetic variant in the small integral membrane protein 1 (SMIM1) and the general population, leveraging data from five cohorts. Metabolic characterization of SMIM1-/- individuals was performed using plasma biochemistry, calorimetric chamber, and DXA scan. FINDINGS We found that individuals homozygous for a loss-of-function genetic variant in SMIM1 gene, underlying the blood group Vel, display excess body weight, dyslipidemia, altered leptin to adiponectin ratio, increased liver enzymes, and lower thyroid hormone levels. This was accompanied by a reduction in resting energy expenditure. CONCLUSION This research identified a novel genetic predisposition to being overweight or obese. It highlights the need to investigate the genetic causes of obesity to select the most appropriate treatment given the large cost disparity between them. FUNDING This work was funded by the National Institute of Health Research, British Heart Foundation, and NHS Blood and Transplant.
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Affiliation(s)
- Luca Stefanucci
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; British Heart Foundation, Cambridge Centre for Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Camous Moslemi
- Department of Clinical Immunology, Zealand University Hospital (Roskilde University), Køge, Denmark
| | - Ana R Tomé
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Samuel Virtue
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Guillaume Bidault
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, MDU MRC, Addenbrooke's Hospital, Cambridge, UK
| | - Nicholas S Gleadall
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Laura P E Watson
- NIHR Cambridge Clinical Research Facility, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Jing E Kwa
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Frances Burden
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Samantha Farrow
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Ji Chen
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Faculty of Health and Life Sciences RILD Building, Barrack Road, Exeter, UK
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Keith Burling
- NIHR Cambridge Biomedical Research Centre Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lindsay Walker
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - John Ord
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Peter Barker
- NIHR Cambridge Biomedical Research Centre Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - James Warner
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Amy Frary
- NIHR National BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Karola Renhstrom
- NIHR National BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Sofie E Ashford
- NIHR National BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Jo Piper
- NIHR Cambridge Clinical Research Facility, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Gail Biggs
- NIHR Cambridge Clinical Research Facility, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Wendy N Erber
- Discipline of Pathology and Laboratory Science, School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia
| | - Gary J Hoffman
- Discipline of Pathology and Laboratory Medicine, Medical School, The University of Western Australia, Perth, WA, Australia
| | - Nadia Schoenmakers
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus University, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Klaus Rieneck
- Department of Clinical Immunology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Morten H Dziegiel
- Department of Clinical Immunology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | | | - Vian Azzu
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK; Department of Gastroenterology, Norfolk & Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Michele Vacca
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK; Interdisciplinary Department of Medicine, Università degli Studi di Bari "Aldo Moro", Bari, Italy; Roger Williams Institute of Hepatology, London, UK
| | | | - Qin Hui
- Atlanta VA Medical Center, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yan V Sun
- Atlanta VA Medical Center, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Peter W Wilson
- Atlanta VA Medical Center, Decatur, GA, USA; Emory University Schools of Medicine and Public Health, Atlanta, GA, USA
| | - Omer A Bayraktar
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Antonio Vidal-Puig
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, MDU MRC, Addenbrooke's Hospital, Cambridge, UK; Centro de Innvestigacion Principe Felipe, Valencia, Spain
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - William J Astle
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; British Heart Foundation, Cambridge Centre for Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; MRC Biostatistics Unit, East Forvie Building, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Martin L Olsson
- Clinical Immunology and Transfusion Medicine, Office for Medical Services, Region Skåne, Lund, Sweden; Department of Laboratory Medicine, Division of Hematology and Transfusion Medicine, Lund University, Lund, Sweden
| | - Jill R Storry
- Clinical Immunology and Transfusion Medicine, Office for Medical Services, Region Skåne, Lund, Sweden; Department of Laboratory Medicine, Division of Hematology and Transfusion Medicine, Lund University, Lund, Sweden
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital (Roskilde University), Køge, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Willem H Ouwehand
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; Department of Haematology, Cambridge University Hospitals NHS Trust, CB2 0QQ Cambridge, UK; Department of Haematology, University College London Hospitals NHS Trust, NW1 2BU London, UK
| | - Krishna Chatterjee
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Dragana Vuckovic
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; British Heart Foundation, Cambridge Centre for Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Faculty of Health and Life Sciences RILD Building, Barrack Road, Exeter, UK.
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Huang M, Lyu C, Liu N, Nembhard WN, Witte JS, Hobbs CA, Li M. A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects. Genet Epidemiol 2023; 47:475-495. [PMID: 37341229 DOI: 10.1002/gepi.22533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/13/2023] [Accepted: 06/02/2023] [Indexed: 06/22/2023]
Abstract
The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.
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Affiliation(s)
- Manyan Huang
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Chen Lyu
- Department of Population Health, New York University Grossman School of Medicine, New York City, New York, USA
| | - Nianjun Liu
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Wendy N Nembhard
- Department of Epidemiology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University, Stanford, California, USA
- Department of Biomedical Data Sciences, Stanford University, Stanford, California, USA
| | - Charlotte A Hobbs
- Rady Children's Institute for Genomic Medicine, San Diego, California, USA
| | - Ming Li
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
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Abstract
Summary
Pregnancy, childbirth and motherhood are new situations for women and require adjustment. Women suffering from schizophrenia require special attention due to the course of the disease. Physiological changes that occur in the body during pregnancy may be unacceptable for women suffering from schizophrenia. They may delusively deny the existence of the pregnancy, lead an unhealthy lifestyle (stimulants, poor diet, lack of gynaecological check-ups), which in turn causes an increased risk of complications. In the research conducted so far, it has been proven that three kinds of complications are associated with schizophrenia: complications concerning pregnancy itself (bleeding, diabetes, Rh-incompatibility, pre-eclampsia), intrauterine growth restriction (low birth weight, congenital malformations, small head circumference) and complications regarding labour (uterine atony, asphyxia, emergency Caesarean section). The course of the labour itself in this specific group of patients has not yet been sufficiently examined. It has also been proven that perinatal complications are one of the factors determining an increased risk of schizophrenia.
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Clark MM, Chazara O, Sobel EM, Gjessing HK, Magnus P, Moffett A, Sinsheimer JS. Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes. Hum Hered 2017; 81:181-193. [PMID: 28214848 DOI: 10.1159/000456033] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Accepted: 01/11/2017] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND/AIMS Maternal and offspring cell contact at the site of placentation presents a plausible setting for maternal-fetal genotype (MFG) interactions affecting fetal growth. We test hypotheses regarding killer cell immunoglobulin-like receptor (KIR) and HLA-C MFG effects on human birth weight by extending the quantitative MFG (QMFG) test. METHODS Until recently, association testing for MFG interactions had limited applications. To improve the ability to test for these interactions, we developed the extended QMFG test, a linear mixed-effect model that can use multi-locus genotype data from families. RESULTS We demonstrate the extended QMFG test's statistical properties. We also show that if an offspring-only model is fit when MFG effects exist, associations can be missed or misattributed. Furthermore, imprecisely modeling the effects of both KIR and HLA-C could result in a failure to replicate if these loci's allele frequencies differ among populations. To further illustrate the extended QMFG test's advantages, we apply the extended QMFG test to a UK cohort study and the Norwegian Mother and Child Cohort (MoBa) study. CONCLUSION We find a significant KIR-HLA-C interaction effect on birth weight. More generally, the QMFG test can detect genetic associations that may be missed by standard genome-wide association studies for quantitative traits.
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Affiliation(s)
- Michelle M Clark
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
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5
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Cui Y, Yang H. Dissecting genomic imprinting and genetic conflict from a game theory prospective: Comment on: "Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition" by Qian Wang et al. Phys Life Rev 2017; 20:161-163. [PMID: 28159530 DOI: 10.1016/j.plrev.2017.01.028] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 01/27/2017] [Indexed: 01/11/2023]
Affiliation(s)
- Yuehua Cui
- Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, United States.
| | - Haitao Yang
- Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, United States
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6
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Clark MM, Blangero J, Dyer TD, Sobel EM, Sinsheimer JS. The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions. Ann Hum Genet 2015; 80:63-80. [PMID: 26567478 DOI: 10.1111/ahg.12137] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 09/11/2015] [Indexed: 12/18/2022]
Abstract
Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered.
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Affiliation(s)
- Michelle M Clark
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas, Rio Grande Valley, Brownsville, TX, USA
| | - Thomas D Dyer
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas, Rio Grande Valley, Brownsville, TX, USA
| | - Eric M Sobel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Janet S Sinsheimer
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.,Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
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7
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Zhang YH, Van Hove JL, McCabe ER, Dipple KM. Gestational Diabetes Associated with a Novel Mutation (378-379insTT) in the Glycerol Kinase Gene. Mol Genet Metab Rep 2015; 4:42-45. [PMID: 26309814 PMCID: PMC4545508 DOI: 10.1016/j.ymgmr.2015.06.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Glycerol kinase deficiency (GKD) is an X-linked inborn error of metabolism at the interface of fat and carbohydrate metabolism. We report a male patient with GKD and a novel insertion of TT in exon 5 at position 378 of the GK cDNA (378–379insTT). This resulted in a premature stop codon and 0.8% normal GK activity. The mother is a carrier for this mutation and had gestational diabetes requiring insulin during this pregnancy but not in her previous pregnancy. Given the association between GKD and type 2 diabetes mellitus, it is interesting that the mother had gestational diabetes while carrying an affected fetus. Therefore, GKD is another disease where there may be a maternal–fetal interaction based on genotype. Further investigations may help elucidate the role of GKD in the carrier mother's gestational diabetes. In addition, these studies will provide better-informed counseling to families with GKD regarding the risk to carrier females.
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Affiliation(s)
- Yao H. Zhang
- Department of Pediatrics, David Geffen School of Medicine at UCLA, and Mattel Children's Hospital UCLA, Los Angeles, CA 90095-1752, USA
| | - Johan L. Van Hove
- Department of Pediatrics, Catholic University Leuven, Leuven B3000, Belgium
| | - Edward R.B. McCabe
- Department of Pediatrics, David Geffen School of Medicine at UCLA, and Mattel Children's Hospital UCLA, Los Angeles, CA 90095-1752, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7088, USA
- Interdepartmental Program, Biomedical Engineering, Henry Samulei School of Engineering and Applied Sciences at UCLA, Los Angeles, CA 90095, USA
| | - Katrina M. Dipple
- Department of Pediatrics, David Geffen School of Medicine at UCLA, and Mattel Children's Hospital UCLA, Los Angeles, CA 90095-1752, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7088, USA
- Interdepartmental Program, Biomedical Engineering, Henry Samulei School of Engineering and Applied Sciences at UCLA, Los Angeles, CA 90095, USA
- Corresponding author at: Departments of Human Genetics and Pediatrics, David Geffen School of Medicine at UCLA, Gonda Center 5506B, 695 Charles E. Young Drive South, Los Angeles, CA 90095-7088, USA.
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Li M, Cleves MA, Mallick H, Erickson SW, Tang X, Nick TG, Macleod SL, Hobbs CA. A genetic association study detects haplotypes associated with obstructive heart defects. Hum Genet 2014; 133:1127-38. [PMID: 24894164 PMCID: PMC4313870 DOI: 10.1007/s00439-014-1453-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Accepted: 05/20/2014] [Indexed: 10/25/2022]
Abstract
The development of congenital heart defects (CHDs) involves a complex interplay between genetic variants, epigenetic variants, and environmental exposures. Previous studies have suggested that susceptibility to CHDs is associated with maternal genotypes, fetal genotypes, and maternal-fetal genotype (MFG) interactions. We conducted a haplotype-based genetic association study of obstructive heart defects (OHDs), aiming to detect the genetic effects of 877 SNPs involved in the homocysteine, folate, and transsulfuration pathways. Genotypes were available for 285 mother-offspring pairs with OHD-affected pregnancies and 868 mother-offspring pairs with unaffected pregnancies. A penalized logistic regression model was applied with an adaptive least absolute shrinkage and selection operator (lasso), which dissects the maternal effect, fetal effect, and MFG interaction effects associated with OHDs. By examining the association between 140 haplotype blocks, we identified 9 blocks that are potentially associated with OHD occurrence. Four haplotype blocks, located in genes MGMT, MTHFS, CBS, and DNMT3L, were statistically significant using a Bayesian false-discovery probability threshold of 0.8. Two blocks in MGMT and MTHFS appear to have significant fetal effects, while the CBS and DNMT3L genes may have significant MFG interaction effects.
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Affiliation(s)
- Ming Li
- Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way Mail Slot 512-40, Little Rock, AR 72202, USA
| | - Mario A. Cleves
- Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way Mail Slot 512-40, Little Rock, AR 72202, USA
| | - Himel Mallick
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Stephen W. Erickson
- Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR 72202, USA
| | - Xinyu Tang
- Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way Mail Slot 512-40, Little Rock, AR 72202, USA
| | - Todd G. Nick
- Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way Mail Slot 512-40, Little Rock, AR 72202, USA
| | - Stewart L. Macleod
- Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way Mail Slot 512-40, Little Rock, AR 72202, USA
| | - Charlotte A. Hobbs
- Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way Mail Slot 512-40, Little Rock, AR 72202, USA
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Li M, Erickson SW, Hobbs CA, Li J, Tang X, Nick TG, Macleod SL, Cleves MA. Detecting maternal-fetal genotype interactions associated with conotruncal heart defects: a haplotype-based analysis with penalized logistic regression. Genet Epidemiol 2014; 38:198-208. [PMID: 24585533 DOI: 10.1002/gepi.21793] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2013] [Revised: 12/18/2013] [Accepted: 01/02/2014] [Indexed: 01/10/2023]
Abstract
Nonsyndromic congenital heart defects (CHDs) develop during embryogenesis as a result of a complex interplay between environmental exposures, genetics, and epigenetic causes. Genetic factors associated with CHDs may be attributed to either independent effects of maternal or fetal genes, or the intergenerational interactions between maternal and fetal genes. Detecting gene-by-gene interactions underlying complex diseases is a major challenge in genetic research. Detecting maternal-fetal genotype (MFG) interactions and differentiating them from the maternal/fetal main effects has presented additional statistical challenges due to correlations between maternal and fetal genomes. Traditionally, genetic variants are tested separately for maternal/fetal main effects and MFG interactions on a single-locus basis. We conducted a haplotype-based analysis with a penalized logistic regression framework to dissect the genetic effect associated with the development of nonsyndromic conotruncal heart defects (CTD). Our method allows simultaneous model selection and effect estimation, providing a unified framework to differentiate maternal/fetal main effect from the MFG interaction effect. In addition, the method is able to test multiple highly linked SNPs simultaneously with a configuration of haplotypes, which reduces the data dimensionality and the burden of multiple testing. By analyzing a dataset from the National Birth Defects Prevention Study (NBDPS), we identified seven genes (GSTA1, SOD2, MTRR, AHCYL2, GCLC, GSTM3, and RFC1) associated with the development of CTDs. Our findings suggest that MFG interactions between haplotypes in three of seven genes, GCLC, GSTM3, and RFC1, are associated with nonsyndromic conotruncal heart defects.
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Affiliation(s)
- Ming Li
- Department of Pediatrics University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America
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Tsang KM, Croen LA, Torres AR, Kharrazi M, Delorenze GN, Windham GC, Yoshida CK, Zerbo O, Weiss LA. A genome-wide survey of transgenerational genetic effects in autism. PLoS One 2013; 8:e76978. [PMID: 24204716 PMCID: PMC3811986 DOI: 10.1371/journal.pone.0076978] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2013] [Accepted: 08/28/2013] [Indexed: 12/15/2022] Open
Abstract
Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (P<10−4) that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4, and SDK1. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.
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Affiliation(s)
- Kathryn M. Tsang
- Department of Psychiatry and Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America
| | - Lisa A. Croen
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Anthony R. Torres
- Center for Persons with Disabilities, Utah State University, Logan, Utah, United States of America
| | - Martin Kharrazi
- Genetic Disease Screening Program, California Department of Health Services, Richmond, California, United States of America
| | - Gerald N. Delorenze
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Gayle C. Windham
- Division of Environmental and Occupational Disease Control, California Department of Health Services, Richmond, California, United States of America
| | - Cathleen K. Yoshida
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Ousseny Zerbo
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Lauren A. Weiss
- Department of Psychiatry and Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America
- * E-mail:
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Howey R, Cordell HJ. PREMIM and EMIM: tools for estimation of maternal, imprinting and interaction effects using multinomial modelling. BMC Bioinformatics 2012; 13:149. [PMID: 22738121 PMCID: PMC3464602 DOI: 10.1186/1471-2105-13-149] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2012] [Accepted: 06/09/2012] [Indexed: 01/28/2023] Open
Abstract
Background Here we present two new computer tools, PREMIM and EMIM, for the estimation of parental and child genetic effects, based on genotype data from a variety of different child-parent configurations. PREMIM allows the extraction of child-parent genotype data from standard-format pedigree data files, while EMIM uses the extracted genotype data to perform subsequent statistical analysis. The use of genotype data from the parents as well as from the child in question allows the estimation of complex genetic effects such as maternal genotype effects, maternal-foetal interactions and parent-of-origin (imprinting) effects. These effects are estimated by EMIM, incorporating chosen assumptions such as Hardy-Weinberg equilibrium or exchangeability of parental matings as required. Results In application to simulated data, we show that the inference provided by EMIM is essentially equivalent to that provided by alternative (competing) software packages such as MENDEL and LEM. However, PREMIM and EMIM (used in combination) considerably outperform MENDEL and LEM in terms of speed and ease of execution. Conclusions Together, EMIM and PREMIM provide easy-to-use command-line tools for the analysis of pedigree data, giving unbiased estimates of parental and child genotype relative risks.
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Affiliation(s)
- Richard Howey
- Institute of Genetic Medicine, Newcastle University, Central Parkway, Newcastle upon Tyne NE1 3BZ, UK
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12
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Burd I, Balakrishnan B, Kannan S. Models of fetal brain injury, intrauterine inflammation, and preterm birth. Am J Reprod Immunol 2012; 67:287-94. [PMID: 22380481 DOI: 10.1111/j.1600-0897.2012.01110.x] [Citation(s) in RCA: 179] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2011] [Accepted: 01/23/2012] [Indexed: 01/10/2023] Open
Abstract
Intrauterine infection and inflammation are known risk factors for brain damage in the neonate irrespective of the gestational age. Infection-induced maternal immune activation leads to a fetal inflammatory response mediated by cytokines that has been implicated in the development of not only periventricular leukomalacia and cerebral palsy but also a spectrum of neurodevelopmental disorders such as autism and schizophrenia (Behav Brain Res 2009; 204:313, Ann Neurol 2005; 57:67, Am J Obstet Gynecol 2000; 182:675). A common link among the neurobehavioral disorders associated with intrauterine inflammation appears to be the evidence for immune dysregulation in the developing brain (Behav Brain Res 2009; 204:313). The timing of the immune challenge with respect to the gestational age and neurologic development of the fetus may be crucial in the elicited response (J Neurosci 2006; 26:4752). Studies involving animal models of maternal inflammation serve a key role in elucidation of mechanisms involved in fetal brain injury associated with exposure to the maternal milieu. These animal models have been shown to result in fetal microglial activation, neurotoxicity as well motor deficits and behavioral abnormalities in the offspring (J Neurosci 2006; 26:4752, J Neurosci Res 2010; 88:172, Am J Obstet Gynecol 2009; 201:279, Am J Obstet Gynecol 2008; 199:651). A better understanding of the mechanisms of perinatal brain injury will allow discoveries of novel neuroprotective agents, better outcomes following preterm birth and stratification of fetuses and neonates for therapies in cases of preterm birth, preterm premature rupture of membranes, and chorioamnionitis.
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Affiliation(s)
- Irina Burd
- Department of Gynecology, Johns Hopkins University, Baltimore, MD 20905, USA.
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Freedman D, Deicken R, Kegeles LS, Vinogradov S, Bao Y, Brown AS. Maternal-fetal blood incompatibility and neuromorphologic anomalies in schizophrenia: Preliminary findings. Prog Neuropsychopharmacol Biol Psychiatry 2011; 35:1525-9. [PMID: 21570439 PMCID: PMC3142286 DOI: 10.1016/j.pnpbp.2011.04.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2010] [Revised: 04/21/2011] [Accepted: 04/27/2011] [Indexed: 01/08/2023]
Abstract
Prior research has shown that maternal-fetal Rhesus (Rh) and ABO blood incompatibility increase the risk for schizophrenia. In the present study, the relationship between blood incompatibility and volumes of brain structures previously implicated in schizophrenia was assessed in schizophrenia cases and controls from a large birth cohort. Rh/ABO incompatible cases had significantly reduced cortical gray matter volume compared to compatible cases, a finding which appears to be driven by significant volume reductions in the dorsolateral prefrontal cortex and inferior frontal cortex. Larger hippocampal and putamen volumes were also observed in exposed controls compared to unexposed controls. Although the sample size is small and replications are required, these data suggest that maternal-fetal blood incompatibility may increase the risk for altered brain morphology in both schizophrenia and in controls. The findings also suggest that the larger hippocampal volume in exposed controls may indicate a mechanism of adaptive resilience which diminishes the risk that controls will develop schizophrenia.
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Affiliation(s)
- David Freedman
- Department of Epidemiology, Mailman School of Public Health of Columbia University, New York, NY, USA.
| | - Raymond Deicken
- Department of Psychiatry, University of California - San Francisco, San Francisco, CA
| | - Lawrence S. Kegeles
- Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York State Psychiatric Institute, New York, NY, Department of Radiology, College of Physicians and Surgeons of Columbia University, New York, NY
| | - Sophia Vinogradov
- Department of Psychiatry, University of California - San Francisco, San Francisco, CA
| | - Yuanyuan Bao
- Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York State Psychiatric Institute, New York, NY
| | - Alan S. Brown
- Department of Epidemiology, Mailman School of Public Health of Columbia University, New York, NY, Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York State Psychiatric Institute, New York, NY
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Preti A, Wilson DR. Schizophrenia, cancer and obstetric complications in an evolutionary perspective-an empirically based hypothesis. Psychiatry Investig 2011; 8:77-88. [PMID: 21852982 PMCID: PMC3149115 DOI: 10.4306/pi.2011.8.2.77] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2010] [Accepted: 10/12/2010] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE Patients diagnosed with schizophrenia have reduced fecundity and premature mortality (both accidental and violent) with no obvious compensatory advantages among kin. The prevalence of the disorder is around 0.7/1%, higher than the expected prevalence of spontaneous mutations. Genes favoring schizophrenia may have been positively selected in the environment of evolutionary adaptation. Literature on potential adaptive genes is reviewed within an evolutionary framework. METHODS Literature search on major scientific search engine (PubMed/Medline, Ovid/PsychInfo) on papers aimed at investigating potential pathways justifying a mutation-selection balanced model. Findings are presented with a narrative touch to favor readability and understanding. RESULTS Reduced incidence of cancer in both patients diagnosed with schizophrenia and their siblings was reported worldwide. Such findings are notable given higher cancer risk factors in schizophrenia, i.e., smoking, alcohol abuse, obesity, poor diet, and poor adherence to therapy. Some genes involved in cancer proliferation might as well confer protective advantage in immune-surveillance, inflammation, vascular proliferation or apoptosis that otherwise will adversely affect early neurodevelopment. CONCLUSION Evidence that reduced risk of certain somatic diseases is associated with schizophrenia is quite significant to progress in the evolutionary epidemiological analysis of psychopathology.
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Affiliation(s)
- Antonio Preti
- Centro Medico Genneruxi, via Costantinopoli 42, Cagliari, Italy
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Bourgey M, Healy J, Saint-Onge P, Massé H, Sinnett D, Roy-Gagnon MH. Genome-wide detection and characterization of mating asymmetry in human populations. Genet Epidemiol 2011; 35:526-35. [DOI: 10.1002/gepi.20602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2011] [Revised: 04/22/2011] [Accepted: 05/20/2011] [Indexed: 11/06/2022]
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16
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Brown AS. The environment and susceptibility to schizophrenia. Prog Neurobiol 2011; 93:23-58. [PMID: 20955757 PMCID: PMC3521525 DOI: 10.1016/j.pneurobio.2010.09.003] [Citation(s) in RCA: 451] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2010] [Revised: 09/22/2010] [Accepted: 09/30/2010] [Indexed: 02/07/2023]
Abstract
In the present article the putative role of environmental factors in schizophrenia is reviewed and synthesized. Accumulating evidence from recent studies suggests that environmental exposures may play a more significant role in the etiopathogenesis of this disorder than previously thought. This expanding knowledge base is largely a consequence of refinements in the methodology of epidemiologic studies, including birth cohort investigations, and in preclinical research that has been inspired by the evolving literature on animal models of environmental exposures. This paper is divided into four sections. In the first, the descriptive epidemiology of schizophrenia is reviewed. This includes general studies on incidence, prevalence, and differences in these measures by urban-rural, neighborhood, migrant, and season of birth status, as well as time trends. In the second section, we discuss the contribution of environmental risk factors acting during fetal and perinatal life; these include infections [e.g. rubella, influenza, Toxoplasma gondii (T. gondii), herpes simplex virus type 2 (HSV-2)], nutritional deficiencies (e.g., famine, folic acid, iron, vitamin D), paternal age, fetal/neonatal hypoxic and other obstetric insults and complications, maternal stress and other exposures [e.g. lead, rhesus (Rh) incompatibility, maternal stress]. Other putative neurodevelopmental determinants, including cannabis, socioeconomic status, trauma, and infections during childhood and adolescence are also covered. In the third section, these findings are synthesized and their implications for prevention and uncovering biological mechanisms, including oxidative stress, apoptosis, and inflammation, are discussed. Animal models, including maternal immune activation, have yielded evidence suggesting that these exposures cause brain and behavioral phenotypes that are analogous to findings observed in patients with schizophrenia. In the final section, future studies including new, larger, and more rigorous epidemiologic investigations, and research on translational and clinical neuroscience, gene-environment interactions, epigenetics, developmental trajectories and windows of vulnerability, are elaborated upon. These studies are aimed at confirming observed risk factors, identifying new environmental exposures, elucidating developmental mechanisms, and shedding further light on genes and exposures that may not be identified in the absence of these integrated approaches. The study of environmental factors in schizophrenia may have important implications for the identification of causes and prevention of this disorder, and offers the potential to complement, and refine, existing efforts on explanatory neurodevelopmental models.
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Affiliation(s)
- Alan S Brown
- Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York State Psychiatric Institute, New York, NY 10032, USA.
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17
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Childs EJ, Palmer CGS, Lange K, Sinsheimer JS. Modeling maternal-offspring gene-gene interactions: the extended-MFG test. Genet Epidemiol 2010; 34:512-21. [PMID: 20552637 DOI: 10.1002/gepi.20508] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Maternal-fetal genotype (MFG) incompatibility is an interaction between the genes of a mother and offspring at a particular locus that adversely affects the developing fetus, thereby increasing susceptibility to disease. Statistical methods for examining MFG incompatibility as a disease risk factor have been developed for nuclear families. Because families collected as part of a study can be large and complex, containing multiple generations and marriage loops, we create the Extended-MFG (EMFG) Test, a model-based likelihood approach, to allow for arbitrary family structures. We modify the MFG test by replacing the nuclear-family based "mating type" approach with Ott's representation of a pedigree likelihood and calculating MFG incompatibility along with the Mendelian transmission probability. In order to allow for extension to arbitrary family structures, we make a slightly more stringent assumption of random mating with respect to the locus of interest. Simulations show that the EMFG test has appropriate type-I error rate, power, and precise parameter estimation when random mating holds. Our simulations and real data example illustrate that the chief advantages of the EMFG test over the earlier nuclear family version of the MFG test are improved accuracy of parameter estimation and power gains in the presence of missing genotypes.
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Affiliation(s)
- Erica J Childs
- Department of Biostatistics, University of California, Los Angeles, California, USA
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18
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Detection of fetomaternal genotype associations in early-onset disorders: evaluation of different methods and their application to childhood leukemia. J Biomed Biotechnol 2010; 2010:369534. [PMID: 20617153 PMCID: PMC2896672 DOI: 10.1155/2010/369534] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2009] [Revised: 11/11/2009] [Accepted: 03/15/2010] [Indexed: 11/17/2022] Open
Abstract
Several designs and analytical approaches have been proposed to dissect offspring from maternal genetic contributions to early-onset diseases. However, lack of parental controls halts the direct verification of the assumption of mating symmetry (MS) required to assess maternally-mediated effects. In this study, we used simulations to investigate the performance of existing methods under mating asymmetry (MA) when parents of controls are missing. Our results show that the log-linear, likelihood-based framework using a case-triad/case-control hybrid design provides valid tests for maternal genetic effects even under MA. Using this approach, we examined fetomaternal associations between 29 SNPs in 12 cell-cycle genes and childhood pre-B acute lymphoblastic leukemia (ALL). We identified putative fetomaternal effects at loci CDKN2A rs36228834 (P = .017) and CDKN2B rs36229158 (P = .022) that modulate the risk of childhood ALL. These data further corroborate the importance of the mother's genotype on the susceptibility to early-onset diseases.
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Evidence for maternal-fetal genotype incompatibility as a risk factor for schizophrenia. J Biomed Biotechnol 2010; 2010:576318. [PMID: 20379378 PMCID: PMC2850511 DOI: 10.1155/2010/576318] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2009] [Revised: 02/09/2010] [Accepted: 02/20/2010] [Indexed: 12/22/2022] Open
Abstract
Prenatal/obstetric complications are implicated in schizophrenia susceptibility. Some complications may arise from maternal-fetal genotype incompatibility, a term used to describe maternal-fetal genotype combinations that produce an adverse prenatal environment. A review of maternal-fetal genotype incompatibility studies suggests that schizophrenia susceptibility is increased by maternal-fetal genotype combinations at the RHD and HLA-B loci. Maternal-fetal genotype combinations at these loci are hypothesized to have an effect on the maternal immune system during pregnancy which can affect fetal neurodevelopment and increase schizophrenia susceptibility. This article reviews maternal-fetal genotype incompatibility studies and schizophrenia and discusses the hypothesized biological role of these ‘‘incompatibility genes”. It concludes that research is needed to further elucidate the role of RHD and HLA-B maternal-fetal genotype incompatibility in schizophrenia and to identify other genes that produce an adverse prenatal environment through a maternal-fetal genotype incompatibility mechanism. Efforts to develop more sophisticated study designs and data analysis techniques for modeling maternal-fetal genotype incompatibility effects are warranted.
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Nicodemus KK, Marenco S, Batten AJ, Vakkalanka R, Egan MF, Straub RE, Weinberger DR. Serious obstetric complications interact with hypoxia-regulated/vascular-expression genes to influence schizophrenia risk. Mol Psychiatry 2008; 13:873-7. [PMID: 18195713 DOI: 10.1038/sj.mp.4002153] [Citation(s) in RCA: 132] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The etiology of schizophrenia is thought to include both epistasis and gene-environment interactions. We sought to test whether a set of schizophrenia candidate genes regulated by hypoxia or involved in vascular function in the brain (AKT1, BDNF, CAPON, CHRNA7, COMT, DTNBP1, GAD1, GRM3, NOTCH4, NRG1, PRODH, RGS4, TNF-alpha) interacted with serious obstetric complications to influence risk for schizophrenia. A family-based study of transmission disequilibrium was conducted in 116 trios. Twenty-nine probands had at least one serious obstetric complication (OC) using the McNeil-Sjostrom Scale, and many of the OCs reported were associated with the potential for fetal hypoxia. Analyses were conducted using conditional logistic regression and a likelihood ratio test (LRT) between nested models was performed to assess significance. Of the 13 genes examined, four (AKT1 (three SNPs), BDNF (two SNPs), DTNBP1 (one SNP) and GRM3 (one SNP)) showed significant evidence for gene-by-environment interaction (LRT P-values ranged from 0.011 to 0.037). Although our sample size was modest and the power to detect interactions was limited, we report significant evidence for genes involved in neurovascular function or regulated by hypoxia interacting with the presence of serious obstetric complications to increase risk for schizophrenia.
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Affiliation(s)
- K K Nicodemus
- Genes, Cognition and Psychosis Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
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Palmer CG, Mallery E, Turunen JA, Hsieh HJ, Peltonen L, Lonnqvist J, Woodward JA, Sinsheimer JS. Effect of Rhesus D incompatibility on schizophrenia depends on offspring sex. Schizophr Res 2008; 104:135-45. [PMID: 18692992 PMCID: PMC2572267 DOI: 10.1016/j.schres.2008.06.022] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2008] [Revised: 06/20/2008] [Accepted: 06/29/2008] [Indexed: 01/15/2023]
Abstract
Rhesus D incompatibility increases risk for schizophrenia, with some evidence that risk is limited to male offspring. The purpose of this study is to determine whether risk for schizophrenia due to Rhesus D incompatibility differs by offspring sex using a nuclear family-based candidate gene approach and a meta-analysis approach. The genetic study is based on a sample of 277 nuclear families with RHD genotype data on at least one parent and at least one child diagnosed with schizophrenia or related disorder. Meta-analysis inclusion criteria were (1) well-defined sample of schizophrenia patients with majority born before 1970, (2) Rhesus D incompatibility phenotype or genotype data available on mother and offspring, and by offspring sex. Two of ten studies, plus the current genetic study sample, fulfilled these criteria, for a total of 358 affected males and 226 affected females. The genetic study found that schizophrenia risk for incompatible males was significantly greater than for compatible offspring (p=0.03), while risk for incompatible and compatible females was not significantly different (p=.32). Relative risks for incompatible males and females were not significantly different from each other. Meta-analysis using a larger number of affected males and females supports their difference. Taken together, these results provide further support that risk of schizophrenia due to Rhesus D incompatibility is limited to incompatible males, although a weak female incompatibility effect cannot be excluded. Sex differences during fetal neurodevelopment should be investigated to fully elucidate the etiology of schizophrenia.
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Affiliation(s)
- Christina G.S. Palmer
- Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, CA, 90095, USA, Department of Human Genetics, University of California, Los Angeles, CA, 90095, USA,Corresponding author. UCLA Semel Institute, 760 Westwood Plaza, Rm 47-422, Los Angeles, CA 90095, USA. Tel.: +1 310 794 4796; fax: +1 310 206 4446. E-mail address: (C.G.S. Palmer)
| | - Erin Mallery
- Department of Biostatistics, University of California, Los Angeles, CA, 90095, USA
| | - Joni A. Turunen
- Institute for Molecular Medicine Finland FIMM and National Public Health Institute, 00251 Helsinki, Finland
| | - Hsin-Ju Hsieh
- Genentech Corporation, San Francisco, CA, 94080, USA
| | - Leena Peltonen
- Institute for Molecular Medicine Finland FIMM and National Public Health Institute, 00251 Helsinki, Finland, Department of Medical Genetics, University of Helsinki, 00251 Helsinki, Finland, Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, 02142, USA, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Jouko Lonnqvist
- Department of Mental Health and Alcohol Research, National Public Health Institute, 00251 Helsinki, Finland, Department of Psychiatry, University of Helsinki, 00251 Helsinki, Finland
| | - J. Arthur Woodward
- School of Social Sciences, Humanities and Arts, University of California, Merced, CA, 95344, USA
| | - Janet S. Sinsheimer
- Department of Human Genetics, University of California, Los Angeles, CA, 90095, USA, Department of Biostatistics, University of California, Los Angeles, CA, 90095, USA, Department of Biomathematics, University of California, Los Angeles, CA, 90095 USA
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Parimi N, Tromp G, Kuivaniemi H, Nien JK, Gomez R, Romero R, Goddard KAB. Analytical approaches to detect maternal/fetal genotype incompatibilities that increase risk of pre-eclampsia. BMC MEDICAL GENETICS 2008; 9:60. [PMID: 18598365 PMCID: PMC2474585 DOI: 10.1186/1471-2350-9-60] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2007] [Accepted: 07/03/2008] [Indexed: 01/06/2023]
Abstract
BACKGROUND In utero interactions between incompatible maternal and fetal genotypes are a potential mechanism for the onset or progression of pregnancy related diseases such as pre-eclampsia (PE). However, the optimal analytical approach and study design for evaluating incompatible maternal/offspring genotype combinations is unclear. METHODS Using simulation, we estimated the type I error and power of incompatible maternal/offspring genotype models for two analytical approaches: logistic regression used with case-control mother/offspring pairs and the log-linear regression used with case-parent triads. We evaluated a real dataset consisting of maternal/offspring pairs with and without PE for incompatibility effects using the optimal analysis based on the results of the simulation study. RESULTS We identified a single coding scheme for the incompatibility effect that was equally or more powerful than all of the alternative analysis models evaluated, regardless of the true underlying model for the incompatibility effect. In addition, the log-linear regression was more powerful than the logistic regression when the heritability was low, and more robust to adjustment for maternal or fetal effects. For the PE data, this analysis revealed three genes, lymphotoxin alpha (LTA), von Willebrand factor (VWF), and alpha 2 chain of type IV collagen (COL4A2) with possible incompatibility effects. CONCLUSION The incompatibility model should be evaluated for complications of pregnancy, such as PE, where the genotypes of two individuals may contribute to the presence of disease.
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Affiliation(s)
- Neeta Parimi
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Gerard Tromp
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA
- Department of Neurology, Wayne State University, Detroit, MI, USA
| | - Helena Kuivaniemi
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA
- Department of Surgery, Wayne State University, Detroit, MI, USA
| | - Jyh Kae Nien
- the Perinatology Research Branch, NICHD, NIH, Bethesda, MD, USA
| | - Ricardo Gomez
- the Perinatology Research Branch, NICHD, NIH, Bethesda, MD, USA
- Center for Perinatal Diagnosis and Research, Sotero del Rio Hospital, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Roberto Romero
- the Perinatology Research Branch, NICHD, NIH, Bethesda, MD, USA
| | - Katrina AB Goddard
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
- Center for Health Research, Kaiser Permanente Northwest, 3800 N. Interstate Avenue, Portland, USA
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Devlin B, Klei L, Myles-Worsley M, Tiobech J, Otto C, Byerley W, Roeder K. Genetic liability to schizophrenia in Oceanic Palau: a search in the affected and maternal generation. Hum Genet 2007; 121:675-84. [PMID: 17436020 DOI: 10.1007/s00439-007-0358-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2006] [Accepted: 03/20/2007] [Indexed: 12/22/2022]
Abstract
While liability to schizophrenia (Scz) is due to genetic and environmental factors, specific factors are largely unknown. We postulate a two-hit model for Scz, in which initial liability is generated during fetal brain development: this "hit" is precipitated by environmental stressors biologically interacting with maternal genetic vulnerability to the stress. Additional liability to Scz is generated by individual genetic vulnerability. To evaluate these putative levels of vulnerability, we search in the genome of both affected individuals and their mothers for variation that differs, statistically, from that in the general population. For parental analyses, mothers were treated as "affected," rather than their offspring, and the fathers were treated as "controls". We used a sample from the Palauan population: 175 individuals diagnosed with Scz, broadly defined; 87 mothers and 45 fathers of affected individuals. Pedigree and diagnostic data were available on 2,953 living and deceased subjects. DNA from 553 individuals was genotyped for short tandem repeats (STR) spaced approximately every 10 cM across the genome. We tested for association between affection status and STR alleles; such an approach was reasonable, despite the widely spaced markers, because this population has far-ranging linkage disequilibrium (LD). Results for the truly affected individuals were modest, whereas results from the maternal generation were promising. For a recessive model and a test for excess allele matching across mothers, significant findings occurred for D20S481, D10S1221, D6S1021, D13S317, and D18S976. Regions in which at least two adjacent markers produced substantial association statistics include 2p12-11.2, 2q24.1-32.1, 6q12-14.1, 10q23.2-24.21, 12q23.2-24.21 and 17q23.2-23.3.
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Affiliation(s)
- Bernie Devlin
- Department of Psychiatry, University of Pittsburgh School of Medicine, 3811 O'Hara Street, Pittsburgh, PA 15213, USA.
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Gaughran F, Blizard R, Mohan R, Zammit S, Owen M. Birth order and the severity of illness in schizophrenia. Psychiatry Res 2007; 150:205-10. [PMID: 17292486 DOI: 10.1016/j.psychres.2006.05.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2005] [Revised: 05/11/2006] [Accepted: 05/12/2006] [Indexed: 10/23/2022]
Abstract
A proposed risk factor for schizophrenia is materno-foetal incompatibility. We tested the hypothesis that, in multiply affected families, later born children would exhibit a more severe form of schizophrenia than their older siblings. The effect of birth order on (1) severity of the worst ever episode of illness; (2) deterioration from premorbid level of functioning; (3) age of onset; (4) response to medication; and (5) illness course, was assessed in 150 sibling pairs with schizophrenia and schizoaffective disorder. We found that later birth order reduced the likelihood of regaining the premorbid level of functioning after an acute episode and was also associated with an earlier age of presentation. This study lends some support to the hypothesis that later birth order results in a more severe form of the disorder, although there are other possible explanations for our findings. Further work is needed to explore the possibility of maternal-foetal genotype incompatibility as a risk factor for schizophrenia.
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Affiliation(s)
- Fiona Gaughran
- Department of Psychological Medicine, King's College London, Institute of Psychiatry, De Crespigny Park, Denmark Hill, London, SE5 8AF, United Kingdom.
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Miles JH, Takahashi TN. Lack of association between Rh status, Rh immune globulin in pregnancy and autism. Am J Med Genet A 2007; 143A:1397-407. [PMID: 17508426 DOI: 10.1002/ajmg.a.31846] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Though causes of autism are considered largely genetic, considerable concern remains that exposure to Rh immune globulin (RhIg), which until 2001 in the United States contained the preservative thimerosal, can cause autism. To determine whether mothers of children with autism are more likely to be Rh negative (Rh(-)) or to have received RhIg preserved with thimerosal, which is 49.6% ethyl mercury, we surveyed families of children with an autism spectrum disorder (ASD) ascertained through a University-based autism clinic considered free of ascertainment biases related to type of autism or severity. Between 2004 and 2006, 305 mothers of 321 children with an ASD agreed to participate in a telephone interview. Analysis of complete records including the blood group status and RhIg exposure of 214 families showed that Rh(-) status is no higher in mothers of children with autism than in the general population, exposure to antepartum RhIg, preserved with thimerosal is no higher for children with autism and pregnancies are no more likely to be Rh incompatible. This was also true for autism subgroups defined by behavioral phenotype, gender, IQ, regressive onset, head circumference, dysmorphology, birth status, essential, or complex phenotype. These findings support the consensus that exposure to ethylmercury in thimerosal is not the cause of the increased prevalence of autism. These data are important not only for parents in this country but also for the international health community where thimerosal continues to be used to preserve multi-dose vials which in turn makes vaccines affordable.
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Affiliation(s)
- Judith H Miles
- Thompson Center for Autism and Neurodevelopmental Disorders, and Department of Child Health, University of Missouri Hospitals and Clinics, 1 Hospital Drive, Columbia, MO 65212, USA.
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Hsieh HJ, Palmer CGS, Sinsheimer JS. Allowing for missing data at highly polymorphic genes when testing for maternal, offspring and maternal-fetal genotype incompatibility effects. Hum Hered 2006; 62:165-74. [PMID: 17065817 DOI: 10.1159/000096444] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2006] [Accepted: 08/07/2006] [Indexed: 12/20/2022] Open
Abstract
Genes can be associated with disease through an individual's inherited genotype, the maternal genotype or the interaction between these two. When the gene is highly polymorphic, it is more difficult to identify the gene's functional role than for less polymorphic loci, because different alleles at the locus may be associated with the disease through separate and joint effects from maternal and offspring genotypes. Family-based studies are used to test genetic associations because of their robustness to population stratification. However, parental genotype data are often missing, and omitting incompletely genotyped families is inefficient. Methods have been proposed to accommodate incomplete families in family-based association studies. They are not easily generalized to allow simultaneous examination of offspring allelic, maternal allelic and maternal-fetal genotype (MFG) incompatibility effects. Since many MFG incompatibility effects occur through matching between maternal and offspring's genotypes, we present an identity-by-state (IBS) framework to incorporate incomplete families in the MFG test when modeling genetic effects produced by a polymorphic gene. Using simulations, we examine the MFG test's performance with incomplete parental genotype data and an IBS framework. The MFG test using the IBS framework is immune to population stratification and efficiently uses information from incomplete families.
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Affiliation(s)
- Hsin-Ju Hsieh
- Biostatistics, University of California, Los Angeles, CA, USA
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Palmer CGS, Hsieh HJ, Reed EF, Lonnqvist J, Peltonen L, Woodward JA, Sinsheimer JS. HLA-B maternal-fetal genotype matching increases risk of schizophrenia. Am J Hum Genet 2006; 79:710-5. [PMID: 16960807 PMCID: PMC1592576 DOI: 10.1086/507829] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2006] [Accepted: 07/16/2006] [Indexed: 12/20/2022] Open
Abstract
Schizophrenia and human leukocyte antigen (HLA) matching between couples or between mothers and offspring have independently been associated with prenatal/obstetric complications, including preeclampsia and low birth weight. Here, we report the results of a family-based candidate-gene study that brings together these two disparate lines of research by assessing maternal-fetal genotype matching at HLA-A, -B, and -DRB1 as a risk factor of schizophrenia. We used a conditional-likelihood modeling approach with a sample of 274 families that had at least one offspring with schizophrenia or a related spectrum disorder. A statistically significant HLA-B maternal-fetal genotype-matching effect on schizophrenia was demonstrated for female offspring (P=.01; parameter estimate 1.7 [95% confidence interval 1.22-2.49]). Because the matching effect could be associated with pregnancy complications rather than with schizophrenia per se, these findings are consistent with the neurodevelopmental hypothesis of schizophrenia and with accumulating evidence that the prenatal period is involved in the origins of this disease. Our approach demonstrates how genetic markers can be used to characterize the biology of prenatal risk factors of schizophrenia.
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Affiliation(s)
- Christina G S Palmer
- Department of Psychiatry and Biobehavioral Sciences, University of California-Los Angeles, Los Angeles, CA 90095, USA.
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Zandi PP, Kalaydjian A, Avramopoulos D, Shao H, Fallin MD, Newschaffer CJ. Rh and ABO maternal-fetal incompatibility and risk of autism. Am J Med Genet B Neuropsychiatr Genet 2006; 141B:643-7. [PMID: 16856119 DOI: 10.1002/ajmg.b.30391] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
We hypothesized that maternal-fetal incompatibility at the Rh or ABO loci may contribute to the risk of autism. There are biologically plausible reasons to believe such effects may play a role, and two previous epidemiologic studies have provided suggestive evidence. To further test this hypothesis, we genotyped the Rh and ABO loci in a sample of 389 independent case-parent trios from the AGRE repository and analyzed the data using a modification of the log-linear model for case-parent trios in which the effects of maternal-fetal genotype incompatibility are modeled jointly with the effects of the affected child's or mother's genotypes. We did not find any evidence that incompatibility at the Rh or ABO loci increases the risk of autism. Furthermore, we did not find any evidence for the presence of a high-risk susceptibility allele at or near these two loci operating either through the mother or child.
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Affiliation(s)
- Peter P Zandi
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21205, USA.
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30
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Hsieh HJ, Palmer CGS, Harney S, Newton JL, Wordsworth P, Brown MA, Sinsheimer JS. The v-MFG test: investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability. Genet Epidemiol 2006; 30:333-47. [PMID: 16607625 DOI: 10.1002/gepi.20148] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.
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Affiliation(s)
- Hsin-Ju Hsieh
- Biostatistics, University of California, Los Angeles, CA, USA
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Minassian SL, Palmer CGS, Turunen JA, Paunio T, Lönnqvist J, Peltonen L, Woodward JA, Sinsheimer JS. Incorporating serotypes into family based association studies using the MFG test. Ann Hum Genet 2006; 70:541-53. [PMID: 16759185 DOI: 10.1111/j.1469-1809.2005.00243.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Family based association tests are widely used to detect genetic effects. The focus of this paper is the maternal-fetal genotype (MFG) incompatibility test, a family based association test which can be used to detect genetic effects that contribute to disease, including alleles in the child that increase disease risk, maternal alleles that increase disease risk in the child, and maternal-fetal genotype incompatibilities. Consideration of incomplete data resulting from using serotypes could expand the power of the MFG test for detecting genetic effects. Serotypes may be all that are available in certain families, or preferred because of convenience or low cost, and thus a modification of the MFG test will allow optimal use of such data. The modified MFG likelihood can accommodate the incomplete data that result from using serotypes rather than the corresponding codominant genotypes. The modified MFG test was evaluated with serotypes and genotypes from families with members affected with schizophrenia. In addition, simulation studies were performed. Results of the data analyses and simulation studies showed that serotypes can be used to augment genotypes within a sample, to increase power to detect effects when the candidate gene produces serotypes.
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Preti A. Obstetric complications, genetics and schizophrenia. Eur Psychiatry 2006; 20:354. [PMID: 16018930 DOI: 10.1016/j.eurpsy.2005.03.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2005] [Accepted: 03/07/2005] [Indexed: 10/25/2022] Open
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Preti A. Obstetric complications, genetics and psychosis. Eur J Obstet Gynecol Reprod Biol 2006; 126:127-8; author reply 128. [PMID: 16423443 DOI: 10.1016/j.ejogrb.2005.11.046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2005] [Revised: 11/08/2005] [Accepted: 11/09/2005] [Indexed: 11/18/2022]
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Hatfield JS. The genetic basis of hair whorl, handedness, and other phenotypes. Med Hypotheses 2006; 66:708-14. [PMID: 16337093 DOI: 10.1016/j.mehy.2005.10.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2005] [Revised: 10/06/2005] [Accepted: 10/07/2005] [Indexed: 11/20/2022]
Abstract
Evidence is presented that RHD, RHCE, and other RH genes, may be interesting candidates to consider when searching for the genetic basis of hair whorl rotation (i.e., clockwise or counterclockwise), handedness (i.e., right handed, left handed or ambidextrous), speech laterality (i.e., right brained or left brained), speech dyslexia (e.g., stuttering), sexual orientation (i.e., heterosexual, homosexual, bisexual, or transsexual), schizophrenia, bipolar disorder, and autism spectrum disorder. Such evidence involves the need for a genetic model that includes maternal immunization to explain some of the empirical results reported in the literature. The complex polymorphisms present among the maternally immunizing RH genes can then be used to explain other empirical results. Easily tested hypotheses are suggested, based upon genotypic (but not phenotypic) frequencies of the RH genes. In particular, homozygous dominant individuals are expected to be less common or lacking entirely among the alternative phenotypes. If it is proven that RH genes are involved in brain architecture, it will have a profound effect upon our understanding of the development and organization of the asymmetrical vertebrate brain and may eventually lead to a better understanding of the developmental processes which occur to produce the various alternative phenotypes discussed here. In addition, if RH genes are shown to be involved in the production of these phenotypes, then the evolutionary studies can be performed to demonstrate the beneficial effect of the recessive alleles of RHD and RHCE, and why human evolution appears to be selecting for the recessive alleles even though an increase in the frequency of such alleles may imply lower average fecundity among some individuals possessing them.
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Affiliation(s)
- Jeff S Hatfield
- USGS Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, MD 20708, USA.
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Insel BJ, Brown AS, Bresnahan MA, Schaefer CA, Susser ES. Maternal-fetal blood incompatibility and the risk of schizophrenia in offspring. Schizophr Res 2005; 80:331-42. [PMID: 16006103 DOI: 10.1016/j.schres.2005.06.005] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2004] [Revised: 05/26/2005] [Accepted: 06/06/2005] [Indexed: 10/25/2022]
Abstract
OBJECTIVE Predicated on a maternal immune response to paternally inherited foreign fetal blood antigens, we hypothesized that maternal-fetal blood incompatibility increases susceptibility to schizophrenia in the offspring. The relation between schizophrenia and maternal-fetal blood incompatibility, arising from the D antigen of the Rhesus (Rh) and the ABO blood group antigens, was examined in a cohort of live-births. METHOD The data were drawn from the Prenatal Determinants of Schizophrenia Study, a cohort of births occurring between 1959 and 1967 to women enrolled in a Kaiser Permanente Plan-Northern California Region (KP). Adult offspring belonging to the KP from 1981 to 1997 were followed for the incidence of schizophrenia spectrum disorder (SSD). Cox proportional hazards regression was the primary analytic technique. RESULTS Among second and later born offspring, the adjusted incidence rate ratio (RR(adj)) of SSD was 1.80 (95% CI=0.71-4.58) for the Rh incompatible offspring compared with the Rh compatible offspring; with the males exhibiting higher rate ratio (RR(adj)=2.37; 95% CI=0.82-6.86) than the females (RR(adj)=0.93 95% CI=0.12-7.01). Among all offspring, the RR(adj) for ABO incompatibility was lower and the elevated rate ratio was similarly limited to the males (RR(adj)=1.68; 95% CI=0.76-3.70). For Rh and/or ABO incompatibility, the RR(adj) was 1.57 (95% CI=0.87-2.82). A statistically significant result was detected only for the male offspring (RR(adj)=2.22; 95% CI=1.10-4.47). CONCLUSION Although the results should be interpreted with caution given the few events of SSD, the findings extend the line of evidence that maternal-fetal blood incompatibility is a risk factor for schizophrenia spectrum disorder; with the strongest evidence to date implicating that the susceptibility pertains only to male offspring.
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Affiliation(s)
- Beverly J Insel
- Mailman School of Public Health of Columbia University Epidemiology, 722 W. 168 St., NY 10032, USA.
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Mitchell LE, Weinberg CR. Evaluation of offspring and maternal genetic effects on disease risk using a family-based approach: the "pent" design. Am J Epidemiol 2005; 162:676-85. [PMID: 16093287 DOI: 10.1093/aje/kwi249] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Diseases that develop during gestation may be influenced by the genotype of the mother and the inherited genotype of the embryo/fetus. However, given the correlation between maternal and offspring genotypes, differentiating between inherited and maternal genetic effects is not straightforward. The two-step transmission disequilibrium test was the first, family-based test proposed for the purpose of differentiating between maternal and offspring genetic effects. However, this approach, which requires data from "pents" comprising an affected child, mother, father, and maternal grandparents, provides biased tests for maternal genetic effects when the offspring genotype is associated with disease. An alternative approach based on transmissions from grandparents provides unbiased tests for maternal and offspring genetic effects but requires genotype information for paternal grandparents in addition to pents. The authors have developed two additional, pent-based approaches for the evaluation of maternal and offspring genetic effects. One approach requires the assumption of genetic mating type symmetry (pent-1), whereas the other does not (pent-2). Simulation studies demonstrate that both of these approaches provide valid estimation and testing for offspring and maternal genotypic effects. In addition, the power of the pent-1 approach is comparable with that of the approach based on data using all four grandparents.
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Affiliation(s)
- Laura E Mitchell
- Center for Environmental and Genetic Medicine, Institute of Biosciences and Technology, Texas AandM University System Health Sciences Center, Houston, TX 77030, USA.
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Minassian SL, Palmer CGS, Sinsheimer JS. An exact maternal-fetal genotype incompatibility (MFG) test. Genet Epidemiol 2005; 28:83-95. [PMID: 15368616 DOI: 10.1002/gepi.20027] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The maternal-fetal genotype incompatibility (MFG) test can be used for a variety of genetic applications concerning disease risk in offspring including testing for the presence of alleles that act directly through offspring genotypes (child allelic effects), alleles that act through maternal genotypes (maternal allelic effects), or maternal-fetal genotype incompatibilities. The log-linear version of the MFG model divides the genotype data into many cells, where each cell represents one of the possible mother, father, and child genotype combinations. Currently, tests of hypotheses about different allelic effects are accomplished by an asymptotic MFG test, but it is unknown if this is appropriate under conditions that produce small cell counts. In this report, we develop an exact MFG test that is based on the permutation distribution of cell counts. We determine by simulation the type I error and power of both the exact MFG test and the asymptotic MFG test for four different biologically relevant scenarios: a test of child allelic effects in the presence of maternal allelic effects, a test of maternal allelic effects in the presence of child allelic effects, and tests of maternal-fetal genotype incompatibility with and without child allelic effects. These simulations show that, in general, the exact test is slightly conservative whereas the asymptotic test is slightly anti-conservative. However, the asymptotic MFG test produces significantly inflated type I error rates under conditions with extreme null allele frequencies and sample sizes of 75, 100, and 150. Under these conditions, the exact test is clearly preferred over the asymptotic test. Under all other conditions that we tested, the user can safely choose either the exact test or the asymptotic test.
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Affiliation(s)
- Sonia L Minassian
- Department of Biostatistics, University of California, Los Angeles, California 90095-1766, USA
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Abstract
Schizophrenia is a serious mental illness that causes major disability and psychosocial impairment. Recent advances in the neurosciences are prompting considerations of schizophrenia from a preventive perspective. An overview of the literature is provided on two important aspects of the development of a prevention orientation in schizophrenia research: elucidation of potential causal risk factors for schizophrenia and research on risk markers. Risk factors for schizophrenia include, but are not limited to, family history, older paternal age, velo-cardio-facial syndrome, maternal infections during pregnancy, pregnancy and delivery complications, and social adjustment difficulties in childhood and adolescence. Potential risk markers include structural brain pathology, minor physical anomalies and dermatoglyphic abnormalities, neurocognitive deficits, eye-tracking dysfunction, certain electrophysiologic findings, and olfactory identification deficits. Several early efforts at indicated preventive interventions targeting individuals at particularly high risk for developing the disorder are discussed. The preventive medicine and public health disciplines may have a role in future research and interventions that apply a preventive perspective to schizophrenia and other mental illnesses. Like any other chronic medical condition, schizophrenia can be considered from a preventive perspective.
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Affiliation(s)
- Michael T Compton
- Emory University School of Medicine, Department of Psychiatry and Behavioral Sciences, Atlanta, Georgia 30303, USA.
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Kraft P, Palmer CGS, Woodward AJ, Turunen JA, Minassian S, Paunio T, Lönnqvist J, Peltonen L, Sinsheimer JS. RHD maternal–fetal genotype incompatibility and schizophrenia: extending the MFG test to include multiple siblings and birth order. Eur J Hum Genet 2004; 12:192-8. [PMID: 14735156 DOI: 10.1038/sj.ejhg.5201129] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Rh incompatibility disease (ie Rh hemolytic disease of the fetus and newborn) has been implicated as a risk factor for schizophrenia. Here, we extend the maternal-fetal genotype incompatibility (MFG) test used in an earlier case-parent trio study that found significant evidence for an increased risk of schizophrenia in RHD MFG-incompatible children. We modify the MFG test for case-parent trios to include any number of siblings. This modified test enables us to use more of the available data from the earlier study. The increased sample size not only gives us greater power to test for MFG incompatibility but it also enables us to model the impact of previous RHD MFG-incompatible pregnancies on the relative risk of RHD MFG incompatibility in later-born siblings. This modeling is important, because RHD MFG incompatibility is a proxy for Rh incompatibility disease, and the risk of Rh incompatibility disease increases with the number of previous RHD MFG-incompatible pregnancies. The best-fitting models are consistent with the hypothesized effect that previous incompatible pregnancies increase the risk of schizophrenia due to RHD MFG incompatibility. There was significant evidence that the relative risk of schizophrenia in the second- and later-born RHD MFG-incompatible children is 1.7, consistent with earlier estimates. Our extension of the MFG test has general application to family-based studies of maternal-genotype and MFG interaction effects.
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Affiliation(s)
- Peter Kraft
- Department of Epidemiology and Biostatistics, Harvard School of Public Health, University of California, Los Angeles, USA.
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Sinsheimer JS, Palmer CGS, Woodward JA. Detecting genotype combinations that increase risk for disease: maternal-fetal genotype incompatibility test. Genet Epidemiol 2003; 24:1-13. [PMID: 12508251 DOI: 10.1002/gepi.10211] [Citation(s) in RCA: 67] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Biological mechanisms that involve gene-by-environment interactions have been hypothesized to explain susceptibility to complex familial disorders. Current research provides compelling evidence that one environmental factor, which acts prenatally to increase susceptibility, arises from a maternal-fetal genotype incompatibility. Because it is genetic in origin, a maternal-fetal incompatibility is one possible source of an adverse environment that can be detected in genetic analyses and precisely studied, even years after the adverse environment was present. Existing statistical models and tests for gene detection are not optimal or even appropriate for identifying maternal-fetal genotype incompatibility loci that may increase the risk for complex disorders. We describe a new test, the maternal-fetal genotype incompatibility (MFG) test, that can be used with case-parent triad data (affected individuals and their parents) to identify loci for which a maternal-fetal genotype incompatibility increases the risk for disease. The MFG test adapts a log-linear approach for case-parent triads in order to detect maternal-fetal genotype incompatibility at a candidate locus, and allows the incompatibility effects to be estimated separately from direct effects of either the maternal or the child's genotype. Through simulations of two biologically plausible maternal-fetal genotype incompatibility scenarios, we show that the type-I error rate of the MFG test is appropriate, that the estimated parameters are accurate, and that the test is powerful enough to detect a maternal-fetal genotype incompatibility of moderate effect size.
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Affiliation(s)
- Janet S Sinsheimer
- Department of Human Genetics, University of California, Los Angeles, California 90095-1766, USA.
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Siegmann AE. A classification of sociomedical health indicators: perspectives for health administrators and health planners. INTERNATIONAL JOURNAL OF HEALTH SERVICES : PLANNING, ADMINISTRATION, EVALUATION 1976; 6:521-38. [PMID: 955757 PMCID: PMC3004532 DOI: 10.2190/my7u-4bgm-9qfy-n0tn] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The conceptualization and operationalization of measures of health status are considered. Health indicators are conceived as a subset of social indicators, and therefore, as any social indicator, they are viewed as derivative from social issues. The interrelationships of different frames of reference for defining and measuring health that have accompained three distinct health problem patterns in the United States are viewed from a developmental perspective. Mortality and morbidity rates, the traditional health indicators, by themselves no longer serve to assess health status in developed nations. Their deficiencies as indicators serve as background for a classification schema for sociomedical health status indicators that relates health definition frames of reference, measures of health status, and health problems. The role of a group of health indicators-sociomedical heath indicators-in the current formulation of health status measures is assessed.
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