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Holla B, Mahadevan J, Ganesh S, Sud R, Janardhanan M, Balachander S, Strom N, Mattheisen M, Sullivan PF, Huang H, Zandi P, Benegal V, Reddy YJ, Jain S, Purushottam M, Viswanath B. A cross ancestry genetic study of psychiatric disorders from India. medRxiv 2024:2024.04.25.24306377. [PMID: 38712191 PMCID: PMC11071591 DOI: 10.1101/2024.04.25.24306377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Genome-wide association studies across diverse populations may help validate and confirm genetic contributions to risk of disease. We estimated the extent of population stratification as well as the predictive accuracy of polygenic scores (PGS) derived from European samples to a data set from India. We analysed 2685 samples from two data sets, a population neurodevelopmental study (cVEDA) and a hospital-based sample of bipolar affective disorder (BD) and obsessive-compulsive disorder (OCD). Genotyping was conducted using Illumina's Global Screening Array. Population structure was examined with principal component analysis (PCA), uniform manifold approximation and projection (UMAP), support vector machine (SVM) ancestry predictions, and admixture analysis. PGS were calculated from the largest available European discovery GWAS summary statistics for BD, OCD, and externalizing traits using two Bayesian methods that incorporate local linkage disequilibrium structures (PGS-CS-auto) and functional genomic annotations (SBayesRC). Our analyses reveal global and continental PCA overlap with other South Asian populations. Admixture analysis revealed a north-south genetic axis within India (FST 1.6%). The UMAP partially reconstructed the contours of the Indian subcontinent. The Bayesian PGS analyses indicates moderate-to-high predictive power for BD. This was despite the cross-ancestry bias of the discovery GWAS dataset, with the currently available data. However, accuracy for OCD and externalizing traits was much lower. The predictive accuracy was perhaps influenced by the sample size of the discovery GWAS and phenotypic heterogeneity across the syndromes and traits studied. Our study results highlight the accuracy and generalizability of newer PGS models across ancestries. Further research, across diverse populations, would help understand causal mechanisms that contribute to psychiatric syndromes and traits.
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Affiliation(s)
- Bharath Holla
- Department of Integrative Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Jayant Mahadevan
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Suhas Ganesh
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Reeteka Sud
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Meghana Janardhanan
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Srinivas Balachander
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Nora Strom
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Manuel Mattheisen
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Dalhousie University, Department of Community Health and Epidemiology & Faculty of Computer Science, Halifax, Nova Scotia, Canada
- University Hospital of Psychiatry and Psychotherapy, University of Bern
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Genetics and Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA02114, USA
| | - Peter Zandi
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Vivek Benegal
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Yc Janardhan Reddy
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Meera Purushottam
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Biju Viswanath
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
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Abok JI, Garver WS, Edwards JS. Bioinformatic analysis of human ZPR1 gene pathogenic exome mutations. bioRxiv 2024:2024.02.27.582196. [PMID: 38464185 PMCID: PMC10925172 DOI: 10.1101/2024.02.27.582196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Advanced sequencing technologies enable rapid detection of sequence variants, aiming to uncover the molecular foundations of human genetic disorders. The challenge lies in interpreting the influence of new exome variants that lead to diverse phenotypes. Our study introduces a detailed, multi-tiered method for assessing the impact of novel variants, particularly focusing on the zinc finger protein 1 (ZPR1) gene. Herein, we employed a combination of variant effect predictors, protein stability analyses, and the American College of Medical Genetics and Association of Molecular Pathology (ACMG/AMP) guidelines. Our structural analysis pinpoints specific amino acid residues in the ZPR1 zinc finger domains that are sensitive to changes, distinguishing between benign and disease-causing coding variants using rigorous in silico tools. We examined 223 germline ZPR1 exome variants, uncovering significant ethnic disparities in the frequency of heterozygous harmful ZPR1 variants, ranging from 0.04% in the Ashkenazi Jewish population to 0.34% in African/African Americans. Additionally, the discovery of three homozygous carriers in European and South Asian groups suggests a higher occurrence of ZPR1 variants in these demographics, meriting further exploration. This research provides insights into the prevalence and implications of amino acid substitutions in the ZPR1 protein.
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Affiliation(s)
- Jeremiah I. Abok
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131-0001, United States
| | - William S. Garver
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131-0001, United States
| | - Jeremy S. Edwards
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131-0001, United States
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Kerdoncuff E, Skov L, Patterson N, Zhao W, Lueng YY, Schellenberg GD, Smith JA, Dey S, Ganna A, Dey AB, Kardia SL, Lee J, Moorjani P. 50,000 years of Evolutionary History of India: Insights from ~2,700 Whole Genome Sequences. bioRxiv 2024:2024.02.15.580575. [PMID: 38405782 PMCID: PMC10888882 DOI: 10.1101/2024.02.15.580575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
India has been underrepresented in whole genome sequencing studies. We generated 2,762 high coverage genomes from India-including individuals from most geographic regions, speakers of all major languages, and tribal and caste groups-providing a comprehensive survey of genetic variation in India. With these data, we reconstruct the evolutionary history of India through space and time at fine scales. We show that most Indians derive ancestry from three ancestral groups related to ancient Iranian farmers, Eurasian Steppe pastoralists and South Asian hunter-gatherers. We uncover a common source of Iranian-related ancestry from early Neolithic cultures of Central Asia into the ancestors of Ancestral South Indians (ASI), Ancestral North Indians (ANI), Austro-asiatic-related and East Asian-related groups in India. Following these admixtures, India experienced a major demographic shift towards endogamy, resulting in extensive homozygosity and identity-by-descent sharing among individuals. At deep time scales, Indians derive around 1-2% of their ancestry from gene flow from archaic hominins, Neanderthals and Denisovans. By assembling the surviving fragments of archaic ancestry in modern Indians, we recover ~1.5 Gb (or 50%) of the introgressing Neanderthal and ~0.6 Gb (or 20%) of the introgressing Denisovan genomes, more than any other previous archaic ancestry study. Moreover, Indians have the largest variation in Neanderthal ancestry, as well as the highest amount of population-specific Neanderthal segments among worldwide groups. Finally, we demonstrate that most of the genetic variation in Indians stems from a single major migration out of Africa that occurred around 50,000 years ago, with minimal contribution from earlier migration waves. Together, these analyses provide a detailed view of the population history of India and underscore the value of expanding genomic surveys to diverse groups outside Europe.
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Affiliation(s)
- Elise Kerdoncuff
- Department of Molecular and Cell Biology, University of California, Berkeley, United States of America
| | - Laurits Skov
- Department of Molecular and Cell Biology, University of California, Berkeley, United States of America
| | - Nick Patterson
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Yuk Yee Lueng
- Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States of America
| | - Gerard D. Schellenberg
- Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States of America
| | - Jennifer A. Smith
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Sharmistha Dey
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, Helsinki, Finland
| | - AB Dey
- Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jinkook Lee
- Department of Economics, and Center for Economic & Social Research, University of Southern California, Los Angeles, California, United States of America
| | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California, Berkeley, United States of America
- Center for Computational Biology, University of California, Berkeley, United States of America
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Andrews SV, Kukkle PL, Menon R, Geetha TS, Goyal V, Kandadai RM, Kumar H, Borgohain R, Mukherjee A, Wadia PM, Yadav R, Desai S, Kumar N, Joshi D, Murugan S, Biswas A, Pal PK, Oliver M, Nair S, Kayalvizhi A, Samson PL, Deshmukh M, Bassi A, Sandeep C, Mandloi N, Davis OB, Roberts MA, Leto DE, Henry AG, Di Paolo G, Muthane U, Das SK, Peterson AS, Sandmann T, Gupta R, Ramprasad VL. The Genetic Drivers of Juvenile, Young, and Early-Onset Parkinson's Disease in India. Mov Disord 2024; 39:339-349. [PMID: 38014556 DOI: 10.1002/mds.29676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 10/18/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Recent studies have advanced our understanding of the genetic drivers of Parkinson's disease (PD). Rare variants in more than 20 genes are considered causal for PD, and the latest PD genome-wide association study (GWAS) identified 90 independent risk loci. However, there remains a gap in our understanding of PD genetics outside of the European populations in which the vast majority of these studies were focused. OBJECTIVE The aim was to identify genetic risk factors for PD in a South Asian population. METHODS A total of 674 PD subjects predominantly with age of onset (AoO) ≤50 years (encompassing juvenile, young, or early-onset PD) were recruited from 10 specialty movement disorder centers across India over a 2-year period; 1376 control subjects were selected from the reference population GenomeAsia, Phase 2. We performed various case-only and case-control genetic analyses for PD diagnosis and AoO. RESULTS A genome-wide significant signal for PD diagnosis was identified in the SNCA region, strongly colocalizing with SNCA region signal from European PD GWAS. PD cases with pathogenic mutations in PD genes exhibited, on average, lower PD polygenic risk scores than PD cases lacking any PD gene mutations. Gene burden studies of rare, predicted deleterious variants identified BSN, encoding the presynaptic protein Bassoon that has been previously associated with neurodegenerative disease. CONCLUSIONS This study constitutes the largest genetic investigation of PD in a South Asian population to date. Future work should seek to expand sample numbers in this population to enable improved statistical power to detect PD genes in this understudied group. © 2023 Denali Therapeutics and The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Shan V Andrews
- Denali Therapeutics, South San Francisco, California, USA
| | - Prashanth L Kukkle
- Manipal Hospital, Bangalore, India
- Parkinson's Disease and Movement Disorders Clinic, Bangalore, India
| | | | | | - Vinay Goyal
- All India Institute of Medical Sciences (AIIMS), New Delhi, India
- Medanta Hospital, New Delhi, India
- Medanta, The Medicity, Gurgaon, India
| | - Rukmini Mridula Kandadai
- Nizams Institute of Medical Sciences (NIMS), Hyderabad, India
- Citi Neuro Centre, Hyderabad, India
| | | | - Rupam Borgohain
- Nizams Institute of Medical Sciences (NIMS), Hyderabad, India
- Citi Neuro Centre, Hyderabad, India
| | - Adreesh Mukherjee
- Bangur Institute of Neurosciences and Institute of Post Graduate Medical Education and Research (IPGME&R), Kolkata, India
| | | | - Ravi Yadav
- National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Soaham Desai
- Department of Neurology, Shree Krishna Hospital and Pramukhaswami Medical College, Bhaikaka University, Anand, India
| | - Niraj Kumar
- All India Institute of Medical Sciences, Rishikesh, India
- All India Institute of Medical Sciences, Bibinagar (Hyderabad Metropolitan Region), Bibinagar, India
| | - Deepika Joshi
- Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | | | - Atanu Biswas
- Bangur Institute of Neurosciences and Institute of Post Graduate Medical Education and Research (IPGME&R), Kolkata, India
| | - Pramod K Pal
- National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | | | | | | | | | | | | | | | | | - Oliver B Davis
- Denali Therapeutics, South San Francisco, California, USA
| | | | - Dara E Leto
- Denali Therapeutics, South San Francisco, California, USA
| | | | | | - Uday Muthane
- Parkinson and Ageing Research Foundation, Bangalore, India
| | - Shymal K Das
- Bangur Institute of Neurosciences and Institute of Post Graduate Medical Education and Research (IPGME&R), Kolkata, India
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Dokuru DR, Horwitz TB, Freis SM, Stallings MC, Ehringer MA. South Asia: The Missing Diverse in Diversity. Behav Genet 2024; 54:51-62. [PMID: 37917228 DOI: 10.1007/s10519-023-10161-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 09/26/2023] [Indexed: 11/04/2023]
Abstract
South Asia, making up around 25% of the world's population, encompasses a wide range of individuals with tremendous genetic and environmental diversity. This region, which spans eight countries, is home to over 4500 anthropologically defined groups that speak numerous languages and have an array of religious beliefs and cultures, making it one of the most diverse places in the world. Much of the region's rich genetic diversity and structure is the result of a complex combination of population history, migration patterns, and endogamous practices. Despite the overwhelming size and diversity, South Asians have often been underrepresented in genetic research, making up less than 2% of the participants in genetic studies. This has led to a lack of population specific understanding of genetic disease risks. We aim to raise awareness about underlying genetic diversity in this ancestry group, call attention to the lack of representation of the group, and to highlight strategies for future studies in South Asians.
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Affiliation(s)
- Deepika R Dokuru
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA.
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.
| | - Tanya B Horwitz
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Samantha M Freis
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Michael C Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Marissa A Ehringer
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
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Xu J, Liu D, Hassan A, Genovese G, Cote AC, Fennessy B, Cheng E, Charney AW, Knowles JA, Ayub M, Peterson RE, Bigdeli TB, Huckins LM. Evaluation of imputation performance of multiple reference panels in a Pakistani population. medRxiv 2023:2023.12.22.23300448. [PMID: 38234809 PMCID: PMC10793543 DOI: 10.1101/2023.12.22.23300448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Genotype imputation is crucial for GWAS, but reference panels and existing benchmarking studies prioritize European individuals. Consequently, it is unclear which publicly available reference panel should be used for Pakistani individuals, and whether ancestry composition or sample size of the panel matters more for imputation accuracy. Our study compared different reference panels to impute genotype data in 1814 Pakistani individuals, finding the best performance balancing accuracy and coverage with meta-imputation with TOPMed and the expanded 1000 Genomes (ex1KG) reference. Imputation accuracy of ex1KG outperformed TOPMed despite its 30-fold smaller sample size, supporting efforts to create future panels with diverse populations.
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Affiliation(s)
- Jiayi Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Dongjing Liu
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Arsalan Hassan
- University of Peshawar, Peshawar, Khyber Pakhtunkhwa, Pakistan
- Institute of Omics and Health Research, Lahore, Pakistan
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Alanna C. Cote
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian Fennessy
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Esther Cheng
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - James A. Knowles
- The Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, USA
| | | | - Roseann E. Peterson
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Tim B. Bigdeli
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Laura M. Huckins
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
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Gupta R. Genetics-based risk scores for prediction of premature coronary artery disease. Indian Heart J 2023; 75:327-334. [PMID: 37633460 PMCID: PMC10568063 DOI: 10.1016/j.ihj.2023.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 07/24/2023] [Accepted: 08/20/2023] [Indexed: 08/28/2023] Open
Abstract
Premature coronary artery disease (CAD) is endemic in India. Global Burden of Diseases study has reported that it led to 286,000 deaths in 2019 in India. Many of these patients have standard risk factors but a third have none. Clinical risk algorithms and imaging provide limited risk information in premature CAD. CAD is multifactorial and studies have now focused on the predictive capability of clusters of genes and single nucleotide polymorphisms (SNPs) using gene risk score (GRS). Older studies combined data from 10 to 12 genes and 100-500 SNPs to calculate GRS, however, following the advent of genome-wide association studies (GWAS), millions of SNPs have been incorporated. Studies have reported that GWAS-based GRS may be more discriminative than conventional tools. Recent studies, especially among South Asians, have reported that GRS improves net reclassification by 15% (12-19%) for younger individuals. Aggressive lifestyle interventions and lipid-lowering therapies can ameliorate risk in high-GRS individuals and potentially prevent premature CAD.
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Affiliation(s)
- Rajeev Gupta
- Department of Preventive Cardiology & Medicine, Eternal Heart Care Centre & Research Institute, Jaipur, India.
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Sahoo SA, Zaidi RA, Anagol S, Mathieson I. Long Runs of Homozygosity Are Correlated with Marriage Preferences across Global Population Samples. Hum Biol 2021; 93:201-216. [PMID: 37701498 PMCID: PMC10497073 DOI: 10.1353/hub.2021.0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Children of consanguineous unions carry long runs of homozygosity (ROH) in their genomes, due to their parents' recent shared ancestry. This increases the burden of recessive disease in populations with high levels of consanguinity and has been heavily studied in some groups. However, there has been little investigation of the broader effect of consanguinity on patterns of genetic variation on a global scale. This study, which collected published genetic data and information about marriage practice from 395 worldwide populations, shows that reported preference for cousin marriage has a detectable association with the distribution of long ROH in this sample, increasing the expected number of ROH longer than 10 cM by a factor of 2.2. Variation in marriage practice and consequent rates of consanguinity are therefore an important aspect of demographic history for the purposes of modeling human genetic variation. However, reported marriage practices explain a relatively small proportion of the variation in ROH distribution, and consequently, population genetic data are only partially informative about cultural preferences.
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Affiliation(s)
- Samali Anova Sahoo
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - rslan A. Zaidi
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Santosh Anagol
- Business Economics and Public Policy, Wharton School of Business, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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