A Neanderthal haplotype introgressed into the human genome confers protection against membranous nephropathy
Authors: Cătălin D. Voinescu, Monika Mozere, Giulio Genovese, Mallory L. Downie, Sanjana Gupta, Daniel P. Gale, Detlef Bockenhauer, Robert Kleta, Mauricio Arcos-Burgos, Horia C. Stanescu
Journal: Kidney International (2024)

Class 2 HLA and PLA2R1 alleles are exceptionally strong genetic risk factors for membranous nephropathy (MN), leading, through an unknown mechanism, to a targeted autoimmune response. Introgressed archaic haplotypes (introduced from an archaic human genome into the modern human genome) might influence phenotypes through gene dysregulation. Here, we investigated the genomic region surrounding the PLA2R1 gene. We reconstructed the phylogeny of Neanderthal and modern haplotypes in this region and calculated the probability of the observed clustering being the result of introgression or common descent. We imputed variants for the participants in our previous genome-wide association study and we compared the distribution of Neanderthal variants between MN cases and controls. The region associated with the lead MN risk locus in the PLA2R1 gene was confirmed and showed that, within a 507 kb region enriched in introgressed sequence, a stringently defined 105 kb haplotype, intersecting the coding regions for PLA2R1 and ITGB6, is inherited from Neanderthals. Thus, introgressed Neanderthal haplotypes overlapping PLA2R1 are differentially represented in MN cases and controls, with enrichment In controls suggesting a protective effect. Class 2 HLA and PLA2R1 alleles are exceptionally strong genetic risk factors for membranous nephropathy (MN), leading, through an unknown mechanism, to a targeted autoimmune response. Introgressed archaic haplotypes (introduced from an archaic human genome into the modern human genome) might influence phenotypes through gene dysregulation. Here, we investigated the genomic region surrounding the PLA2R1 gene. We reconstructed the phylogeny of Neanderthal and modern haplotypes in this region and calculated the probability of the observed clustering being the result of introgression or common descent. We imputed variants for the participants in our previous genome-wide association study and we compared the distribution of Neanderthal variants between MN cases and controls. The region associated with the lead MN risk locus in the PLA2R1 gene was confirmed and showed that, within a 507 kb region enriched in introgressed sequence, a stringently defined 105 kb haplotype, intersecting the coding regions for PLA2R1 and ITGB6, is inherited from Neanderthals. Thus, introgressed Neanderthal haplotypes overlapping PLA2R1 are differentially represented in MN cases and controls, with enrichment In controls suggesting a protective effect. Translational StatementMembranous nephropathy (MN) is an important example of a disorder in which careful molecular analysis furthers the understanding of an autoimmune pathogenetic mechanism. Much progress has been done regarding the qualitative (structural) aspects of antigenicity of the autoantibody, but we believe that this mechanism is complemented by a quantitative (level of expression) component, which still needs further investigation. Our work provides insight into the structure of the genomic region putatively involved in the control of the expression of the major autoantigen in MN. Membranous nephropathy (MN) is an important example of a disorder in which careful molecular analysis furthers the understanding of an autoimmune pathogenetic mechanism. Much progress has been done regarding the qualitative (structural) aspects of antigenicity of the autoantibody, but we believe that this mechanism is complemented by a quantitative (level of expression) component, which still needs further investigation. Our work provides insight into the structure of the genomic region putatively involved in the control of the expression of the major autoantigen in MN. Idiopathic or primary membranous nephropathy (MN) is a rare kidney-specific autoimmune disease. The incidence of MN is 10 to 12 per million persons per year.1Couser W.G. Primary membranous nephropathy.Clin J Am Soc Nephrol. 2017; 12: 983-997Crossref PubMed Scopus (386) Google Scholar,2McGrogan A. Franssen C.F. de Vries C.S. 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No evidence of a Neanderthal contribution to modern human diversity.Genome Biol. 2008; 9: 206Crossref PubMed Google Scholar More recently, compelling evidence has gathered in its favor, mainly starting with the sequencing of the Neanderthal genome.12Prüfer K. Racimo F. Patterson N. et al.The complete genome sequence of a Neanderthal from the Altai mountains.Nature. 2014; 505: 43-49Crossref PubMed Scopus (1365) Google Scholar,13Green R.E. Krause J. Ptak S.E. et al.Analysis of one million base pairs of Neanderthal DNA.Nature. 2006; 444: 330-336Crossref PubMed Scopus (525) Google Scholar,18Vernot B. Akey J.M. Resurrecting surviving Neandertal lineages from modern human genomes.Science. 2014; 343: 1017-1021Crossref PubMed Scopus (379) Google Scholar As a result of the interbreeding, ≈1% to 3% of the H sapiens sapiens genome is believed to be of introgressed Neanderthal origin.12Prüfer K. Racimo F. Patterson N. et al.The complete genome sequence of a Neanderthal from the Altai mountains.Nature. 2014; 505: 43-49Crossref PubMed Scopus (1365) Google Scholar(p201),13Green R.E. Krause J. Ptak S.E. et al.Analysis of one million base pairs of Neanderthal DNA.Nature. 2006; 444: 330-336Crossref PubMed Scopus (525) Google Scholar,19Wall J.D. Yang M.A. Jay F. et al.Higher levels of neanderthal ancestry in East Asians than in Europeans.Genetics. 2013; 194: 199-209Crossref PubMed Scopus (180) Google Scholar,20Sankararaman S. Mallick S. Dannemann M. et al.The genomic landscape of Neanderthal ancestry in present-day humans.Nature. 2014; 507: 354-357Crossref PubMed Scopus (629) Google Scholar with specific loci being particularly prone to originate from the ancient group. 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Sveinbjörnsson G. et al.The nature of Neanderthal introgression revealed by 27,566 Icelandic genomes.Nature. 2020; 582: 78-83Crossref Scopus (49) Google Scholar We investigate a genomic region of ≈1 million bases centered around rs4664308, the lead single-nucleotide polymorphism (SNP) on chromosome 2 from the 2011 MN genome-wide association study (GWAS).9Stanescu H.C. Arcos-Burgos M. Medlar A. et al.Risk HLA-DQA1 and PLA(2)R1 alleles in idiopathic membranous nephropathy.N Engl J Med. 2011; 364: 616-626Crossref PubMed Scopus (418) Google Scholar This region is defined by coordinates chromosome 2:160500000-161500000 (hg19) and harbors the PLA2R1 gene and its 5′ upstream and 3′ downstream regions (Figure 1). Data for 3 Neanderthal genomes (Chagyrskaya 8,32Mafessoni F. Grote S. de Filippo C. et al.A high-coverage Neandertal genome from Chagyrskaya Cave.Proc Natl Acad Sci U S A. 2020; 117: 15132-15136Crossref PubMed Scopus (0) Google Scholar Vindija 33.19,33Prüfer K. de Filippo C. 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The genotyping for the British cohort of the study by Stanescu et al. in 2011 has been performed by deCODE genetics on DNA samples from 335 case patients and 349 ethnically matched controls, as described in the article.9Stanescu H.C. Arcos-Burgos M. Medlar A. et al.Risk HLA-DQA1 and PLA(2)R1 alleles in idiopathic membranous nephropathy.N Engl J Med. 2011; 364: 616-626Crossref PubMed Scopus (418) Google Scholar We used Beagle 5.1 to phase35Browning S.R. Browning B.L. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering.Am J Hum Genet. 2007; 81: 1084-1097Abstract Full Text Full Text PDF PubMed Scopus (2189) Google Scholar and to impute36Browning B.L. Zhou Y. Browning S.R. A One-penny imputed genome from next-generation reference panels.Am J Hum Genet. 2018; 103: 338-348Abstract Full Text Full Text PDF PubMed Scopus (823) Google Scholar variants for the UK participants from our previously published study9Stanescu H.C. Arcos-Burgos M. Medlar A. et al.Risk HLA-DQA1 and PLA(2)R1 alleles in idiopathic membranous nephropathy.N Engl J Med. 2011; 364: 616-626Crossref PubMed Scopus (418) Google Scholar (the parameters used were: burnin = 6, iterations = 12, phase states = 280, imputed states = 1600, imputed segment = 6.0, step = 0.1, imputed nsteps = 7, cluster = 0.005). We used all 2504 genomes from the 1000 Genomes Project (phase 3 release)37Auton A. Brooks L.D. et al.1000 Genomes Project ConsortiumA global reference for human genetic variation.Nature. 2015; 526: 68-74Crossref PubMed Scopus (9898) Google Scholar as the reference panel (see Data Statement). For the preimputation quality control, we filtered the samples by call rate > 0.95, and variants by call rate > 0.99, minor allele frequency > 0.01, and Hardy-Weinberg equilibrium for controls P > 0.0001. We also removed variants that had no variation in either cases or controls. Imputation quality control was performed by removing variants below an R2 threshold of 0.8. We used bcftools 1.10.238Li H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.Bioinforma Oxf Engl. 2011; 27: 2987-2993Crossref PubMed Scopus (0) Google Scholar and tabix 1.10.239Li H. Tabix: fast retrieval of sequence features from generic TAB-delimited files.Bioinforma Oxf Engl. 2011; 27: 718-719Crossref PubMed Scopus (0) Google Scholar to extract the variants within the region of interest, both from the British cohort of the study by Stanescu et al. in 2011 and from the 3 Neanderthal genomes. Variants with known archaic alleles were selected, and linkage disequilibrium (LD) with rs4664308 (the lead SNP from the article by Stanescu et al. in 2011) was estimated with LDproxy (Ldlink 5.1)40Machiela M.J. Chanock S.J. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants.Bioinforma Oxf Engl. 2015; 31: 3555-3557Crossref PubMed Scopus (1110) Google Scholar using the British participants to the 1000 Genomes Project as a reference. We used bcftools to extract haplotypes for the region of high LD from the 1000 Genomes Project and the 3 Neanderthal genomes, including only variants for which data are available in both the 1000 Genomes data set and at least 1 of the Neanderthal genomes, and we converted haplotype data to PHYLIP format with an in-house Python script. We created 2 consensus Neanderthal haplotypes for the variants in the region of interest, at different levels of stringency: a majority consensus by selecting the allele present in most of the known Neanderthal haplotypes at each locus, and a unanimous consensus by selecting only variants where all 3 Neanderthal samples are available, homozygous, and in unanimous agreement. The reconstruction of the phylogeny of the haplotypes from the 1000 Genomes Project in the region of high LD was performed using phyml version 3.3.3 with the default parameters (neighbor joining using the Hasegawa-Kishino-Yano substitution matrix),41Guindon S. Dufayard J.F. Lefort V. et al.New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.Syst Biol. 2010; 59: 307-321Crossref PubMed Scopus (12941) Google Scholar and the resulting trees were visualized with the ETE toolkit42Huerta-Cepas J. Serra F. Bork P. ETE 3: reconstruction, analysis, and visualization of phylogenomic data.Mol Biol Evol. 2016; 33: 1635-1638Crossref PubMed Scopus (1085) Google Scholar and with iTOL.43Letunic I. Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation.Nucleic Acids Res. 2021; 49: W293-W296Crossref PubMed Scopus (3478) Google Scholar Ancestral allele information from Ensembl, as supplied in the 1000 Genomes Project data set, was used for rooting the trees. We used the method published by Huerta-Sánchez et al.44Huerta-Sánchez E. Jin X. Asan et al.Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA.Nature. 2014; 512: 194-197Crossref PubMed Scopus (663) Google Scholar to investigate the likelihood of having an extended haplotype originating from a common ancestor of Neanderthals and present-day humans, as opposed to the introgression hypothesis. We interpolated the local recombination rate to 0.471 cM per Mb (between markers D2S156 and D2S2395) from the data set published by Kong et al.,45Kong A. Gudbjartsson D.F. Sainz J. et al.A high-resolution recombination map of the human genome.Nat Genet. 2002; 31: 241-247Crossref PubMed Scopus (1380) Google Scholar assuming the divergence between Neanderthals and modern humans took place 550,000 years ago,12Prüfer K. Racimo F. Patterson N. et al.The complete genome sequence of a Neanderthal from the Altai mountains.Nature. 2014; 505: 43-49Crossref PubMed Scopus (1365) Google Scholar interbreeding between Neanderthals and modern humans took place ≈50,000 years ago, and the average generational time is 29 years.46Zeberg H. Dannemann M. Sahlholm K. et al.A Neanderthal sodium channel increases pain sensitivity in present-day humans.Curr Biol. 2020; 30: 3465-3469.e4Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar For the cases and controls from the British cohort of the study by Stanescu et al. in 2011, we performed a basic allele test (additive model) on biallelic variants with minor allele frequency > 0.05, as implemented in PLINK 2.0 (www.cog-genomics.org/plink/2.0/).47Chang C.C. Chow C.C. Tellier L.C. et al.Second-generation PLINK: rising to the challenge of larger and richer datasets.GigaScience. 2015; 4: 7Crossref PubMed Scopus (5677) Google Scholar No adjustment for confounders was used, as the cases and controls are ethnically matched. This was verified by primary component analysis (see Supplementary Figure S1). The direction of effect of the alleles was determined using the odds ratio (odds ratio > 1 [risk] and odds ratio < 1 [protective]) for each variant on the imputed data. We grouped variants with a known direction of effect in 3 categories: variants where the risk allele is the consensus Neanderthal allele; variants where the risk allele is the modern allele (i.e., the protective allele is the consensus Neanderthal allele); and variants where the consensus Neanderthal allele is unknown or undefined (no majority). We created an LD plot based on the R2, color coded according to the 3 categories described above. We counted the number of positions where the haplotypes in the study differed from the Neanderthal consensus haplotype and used R version 4.3.1 to decide on the statistical significance of the difference in distribution between cases and controls. We performed detailed functional annotations for all the 1237 variants identified in the introgressed sequence. We used 3 data sets sourced from the University of California, Santa Cruz, Genome Browser48Kent W.J. Sugnet C.W. Furey T.S. et al.The human genome browser at UCSC.Genome Res. 2002; 12: 996-1006Crossref PubMed Scopus (7308) Google Scholar as follows: PhastCons49Siepel A. Bejerano G. Pedersen J.S. et al.Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes.Genome Res. 2005; 15: 1034-1050Crossref PubMed Scopus (2776) Google Scholar Conservation Elements (at a conservation score > 500; range, 0–1000). This allowed us to detect queried SNPs that fall within conserved genomic elements. DnaseI from ENCODE50An integrated encyclopedia of DNA elements in the human genome.Nature. 2012; 489: 57-74Crossref PubMed Scopus (12020) Google Scholar/OpenChrom was used for identifying queried SNPs in accessible, open chromatin regions. Transcription factor chromatin immunoprecipitation–sequencing clusters (spanning 338 factors and 130 cell types) from ENCODE 351Wang J. Zhuang J. Iyer S. et al.Factorbook.org: a Wiki-based database for transcription factor-binding data generated by the ENCODE consortium.Nucleic Acids Res. 2013; 41: D171-D176Crossref PubMed Scopus (216) Google Scholar were used to determine intersections between queried SNPs and transcription factor binding sites. We employed the wANNOVAR52Chang X. Wang K. wANNOVAR: annotating genetic variants for personal genomes via the web.J Med Genet. 2012; 49: 433-436Crossref PubMed Scopus (319) Google Scholar web tool to annotate the functional consequences (missense, synonymous) of all coding variants. The tool also predicted the potential impact on protein sequences based on metrics from SIFT, PolyPhen, CADD, and GERP++ pathogenicity scores. We queried general (GTEx53GTEx ConsortiumThe Genotype-Tissue Expression (GTEx) project.Nat Genet. 2013; 45: 580-585Crossref PubMed Scopus (5095) Google Scholar) and kidney-specific expression quantitative trait loci (eQTL) data sets (NephQTL54Gillies C.E. Putler R. Menon R. et al.An eQTL landscape of kidney tissue in human nephrotic syndrome.Am J Hum Genet. 2018; 103: 232-244Abstract Full Text Full Text PDF PubMed Scopus (118) Google Scholar and the Human Kidney eQTL Atlas55Qiu C. Huang S. Park J. et al.Renal compartment-specific genetic variation analyses identify new pathways in chronic kidney disease.Nat Med. 2018; 24: 1721-1731Crossref PubMed Scopus (143) Google Scholar). In our region of interest, chromosome 2:160500000-161500000 (hg19), we have 102 genotyped variants (post quality control, preimputation) and 4355 variants postimputation at an R2 threshold of 0.8. We found a 105-kb region, chromosome 2:160899566-161004983 (hg19), to be in high (R2 > 0.98) LD with rs4664308, the lead SNP from the 2011 GWAS. A 507-kb region, chromosome 2:160741415-161341364 (hg19), is in moderate LD (R2 > 0.25) with the same SNP (Figure 1, dark and light gray bars). In the phylogenetic tree reconstructed from all 5008 haplotypes from the 1000 Genomes Project and the 3 Neanderthal sequences, we observed clustering of all 3 archaic sequences along with a subset of 1011 modern haplotypes, with a distinctly long branch length and excellent bootstrap support of 1.0 (Figure 2, shaded in gray). The self-declared ancestry of the 1000 Genomes Project participants in this 1011-haplotype cluster was mainly European (411 haplotypes) and East Asian (323 haplotypes). There were 43 haplotypes belonging to individuals of self-declared African ancestry. The clustering and branch lengths show that, in the region of high LD, Neanderthals and some modern humans share a nearly identical haplotype, which is distinct from other haplotypes present in most modern humans. We calculated the expected length of an ancestral haplotype shared by inheritance over a total branch length of 1,050,000 years (t0 = 36,207 generations): L0 = 5864 base pairs. For comparison, the expected length of a haplotype following introgression 50,000 years ago, t1 = 1724 generations, is L1 = 123,142 base pairs. The probability of shared inheritance of an ancestral 105.4-kb haplotype is P0 = 2.96 × 10–7; the shared haplotype is thus almost certainly the result of recent introgression. This is a conservative