Schizophrenia is a debilitating psychiatric disorder associated with a reduced fertility and decreased life expectancy, yet common predisposing variation substantially contributes to the onset of the disorder, which poses an evolutionary paradox. Previous research has suggested balanced selection, a mechanism by which schizophrenia risk alleles could also provide advantages under certain environments, as a reliable explanation. However, recent studies have shown strong evidence against a positive selection of predisposing loci. Furthermore, evolutionary pressures on schizophrenia risk alleles could have changed throughout human history as new environments emerged. Here in this study, we used 1000 Genomes Project data to explore the relationship between schizophrenia predisposing loci and recent natural selection (RNS) signatures after the human diaspora out of Africa around 100,000 years ago on a genome-wide scale. We found evidence for significant enrichment of RNS markers in derived alleles arisen during human evolution conferring protection to schizophrenia. Moreover, both partitioned heritability and gene set enrichment analyses of mapped genes from schizophrenia predisposing loci subject to RNS revealed a lower involvement in brain and neuronal related functions compared to those not subject to RNS. Taken together, our results suggest non-antagonistic pleiotropy as a likely mechanism behind RNS that could explain the persistence of schizophrenia common predisposing variation in human populations due to its association to other non-psychiatric phenotypes. Affecting around 0.5% of the human population4, schizophrenia is associated with increased mortality5 and a low rate of recovery of only 13.5%6. Moreover, schizophrenia has been associated with high rates of comorbid illnesses such as coronary heart disease, stroke, diabetes, respiratory diseases7 and a 15% rate of unnatural deaths, including suicide5.Schizophrenia is a complex mental disorder characterized by psychosis , social and emotional withdrawal, and cognitive deficits. Although the typical onset does not occur until adolescence or early adulthood, epidemiological and molecular evidence has consistently described the early neurodevelopmental nature of the disorder8, thus corroborating the major contribution of genetic variability to the development of the disorder. Although both rare copy number variants (CNVs)9 and disruptive mutations12 importantly contribute to the polygenic architecture of schizophrenia, genome-wide association studies (GWAS) have demonstrated that contribution from common genetic variation  account for up to a half of the genetic variance in liability13. Methods capturing the cumulative risk such as polygenic risk scores (PGS)14 or linkage disequilibrium (LD) score regression (LDSC)15 have demonstrated an uneven distribution of schizophrenia genetic heritability across the genome, with enrichment of synaptic or brain-related pathways18, even though predisposing loci are genome-wide distributed.Family, twin, and adoption studies have estimated schizophrenia heritability to be 65–80%19 and the early mortality associated with schizophrenia5, negative selection should result in the purge of deleterious alleles that contribute to the disorder. However, the persistence of common predisposing alleles and comparable prevalence rates of schizophrenia in human populations suggests an evolutionary paradox21. Some authors have attempted to explain this paradox by balanced selection, by which schizophrenia risk alleles could also provide advantages under certain environments22. In this sense, a recent study described that schizophrenia alleles are linked with creativity in the general population23, thus supporting classical theories that proposed schizophrenia vulnerability as a price to pay for the development of language and abstract or creative thinking25. Recent works, however, have shown strong evidence against a positive selection of predisposing loci28.Given the reduced fertility25. In this context, the study of human populations offers a unique opportunity to address recent natural selection (RNS)30 that has taken place since African populations initiated dispersion into Eurasia around 60,000–100,000 years ago33. A recent study has demonstrated that genetic predisposing variants to schizophrenia exert similar risks across East Asian and European populations, thus pointing to a shared genetic basis for schizophrenia regardless of the ethnic or cultural backgrounds34. However, at the same time, SNPs associated with schizophrenia display greater population differentiation than matched control SNPs29, and some are reportedly even population-specific36. This scenario suggests that recent population differentiation events could have shaped the allelic distribution of schizophrenia polygenic variation across populations.Most of the previous studies addressing the evolutionary nature of schizophrenia lack a clear dynamic perspective of the environment during human evolution. Classical theories stating schizophrenia as a by-product of human ancestral evolution may not be relevant to explain the recent evolution of schizophrenia predisposing allelesloci38, selective forces for other traits could have acted to differentiate human populations across schizophrenia predisposing alleles, thus generating uneven schizophrenia genetic risks across populations. For instance, the risk allele of SLC39A8, a genome-wide significant gene in schizophrenia39, could have arisen after the human expansion to Europe to ease adaptation to colder climates by reducing blood pressure and risk of hypertension40. Older environments, however, could have promoted different genetic adaptations. In this sense, the schizophrenia alleles that have emerged and rose their frequency due to polygenic adaptation after human divergence from Neanderthal 42 may not be adaptative throughout modern environments, and therefore subject to selective pressures in modern humans.Moreover, given the high comorbidity rates of schizophrenia with other mental and somatic conditions and the pleiotropic effects of its predisposing 29. Many of the available methods are based on FST statistical tests, which need an a priori classification of studied individuals in populations43. However, many methods do not account for the hierarchical population structure due to the unequal differentiation within populations, which may lead to detection of many false positives44. Moreover, classification in fixed population groups may be challenging when population ascertainment does not reveal differentiated clusters or individuals are misclassified46. Some individual-based methods performing genome-wide selection sweeps based on principal component analysis (PCA) have been recently developed to address these challenges48.The classical approach to discover RNS signals has consisted of seeking variants with large allele frequency differences between populationspcadapt48, a recently developed PCA-based method, we described a significant association between RNS signatures and schizophrenia. Second, by focusing on the derived alleles arisen during human evolution, we demonstrated a significant trend toward fixation of derived protective alleles. Third, we explored the biological and cell-type enrichments of the RNS markers associated with schizophrenia and observed less brain and neuronal specificity than across markers not subject to RNS. Finally, among the derived alleles arisen during recent evolution, we observed greater pleiotropy for protective than for risk alleles, thus suggesting that recent protective selection to schizophrenia is related to other phenotypes resulting from recent human adaptation to different environments.Here we aimed to perform a comprehensive approach to evaluate the effect of RNS on common genetic variation predisposing to schizophrenia Fig. . First, 31). Pcadapt48 was used to study RNS signals across human populations from 1000 Genomes Project data. Up to 3 principal components (PCs) were kept based on the proportion of variance explained . A marked accumulation of SNPs subject to RNS (pRNS < 0.05) was detected .RNS was characterized across the genome  across the most stringent schizophrenia GWAS thresholds  = 3.45 ; Fig. p-values, we selected the 5% of LD-independent SNPs with the lowest pRNS after LD-clumping based on RNS p-values  = 3.22 ; Fig. 51, a related brain disorder52 that may escape natural selection due to its late onset. LD-clumping was performed based on Alzheimer’s GWAS p-values. No significant enrichment between RNS and Alzheimer’s disease was observed  = 3.45 .51, 4.59) = 3.45 .51, 4.59) = 3.45 .51, 4.59pSCZ < 0.05; NSNPs = 41,079; LD-clumping based on pSCZ) and found a significant correlation . This result was confirmed by conducting 10,000 random permutations of the GWAS results with respect to the pRNS values and testing whether the observed correlation was significantly higher than the null distribution . We repeated this analysis using GWAS data from Alzheimer’s disease and observed no significant correlation with RNS  of schizophrenia across the RNS markers (h2SNP enrichment (CI 95%) = 1.31 (1.13 – 1.50); p = 1.19 × 10–3; Supplementary Data Heritability enrichment analyses using LDSC showed a significant SNP-based heritability enrichment (ment CI 9% = 1.31 SCZ) in an independent case–control cohort . After dividing the resultant schizophrenia predisposing variation into 20-quantiles (NSNPs = 3052) ranked by pRNS, we observed a reduction of the explained variance in the case–control cohort when moving to higher pRNS , distance to nearest gene, and gene density (see Methods). PGSSCZ prediction from the first quantile was found to be significantly higher than the distribution of 1000 predictions from matched SNP selections . Again, a similar reduction of the explained variance towards higher pRNS was found . Also, PGSSCZ prediction from the first quantile was found to be significantly higher than the distribution of 1000 predictions from the remaining SNPs  across the most stringent schizophrenia GWAS thresholds  = 2.76 ; Supplementary Data loci across East Asian-based RNS markers  = 1.65 ; Supplementary Data Following a similar methodology, we considered the 5% of LD-independent SNPs with the lowest p < 1 × 10–16).Moreover, we described a great overlap between European ancestry based and global RNS markers. Across the 46,872 common LD-independent SNPs in both European and all population RNS data, 1176 out of 2249 RNS markers were among the top 5% with highest probability to be RNS marker ). We calculated GWAS derived-ORSCZ referred to the derived allele and evaluated whether RNS markers associated with schizophrenia were enriched for derived alleles conferring risk or protection to the illness.In order to study whether RNS markers confer risk or protection to schizophrenia, we focused on the derived alleles arisen during human evolution . We used LD-independent SNPs with available information of the ancestral allele  in the 1000 Genomes database (N10(derived-ORSCZ) (CI95%) = − 0.052 ; p = 0.031 at PSCZ threshold = 5 × 10–10; Nprotective-SNPs = 7; Nrisk-SNPs = 1; Fig. 10(derived-ORSCZ) (CI95%) = 0.001 ; p = 0.759 at PSCZ threshold = 5 × 10–10; Nprotective-SNPs = 74; Nrisk-SNPs = 69; Fig. We described a significant enrichment of RNS markers for derived alleles with a protective effect on schizophrenia risk at the most stringent GWAS thresholds .Nine out of 13 RNS markers from schizophrenia GWS 55, we evaluated PGSSCZ performance in the independent CIBERSAM case–control sample  for RNS markers and the rest of non-selected SNPs, by considering variants with protective or derived risk alleles separately  and protective (NSNPs = 3168) SNPs subject to RNS, we then conducted PGSSCZ comparisons after using random permutations of 1000 SNPs for each subset of SNPs . The difference in explained variance between risk and protective variants was smaller across non-RNS SNPs . We observed similar MAF across protective (MAF(CI95%) = 0.366 ) and risk (MAF(CI95%) = 0.336 ) RNS markers, thus ruling out that the results could be inflated by higher MAF of risk SNPs.Additionally, as pleiotropy might limit effect sizeloci that were both subject to RNS and associated with schizophrenia. We used LDSC applied to specifically expressed genes (LDSC-SEG) to evaluate the schizophrenia heritability enrichments across RNS markers within 10 different tissues, 13 brain related tissues, and 3 brain cell-types and compared them to the LDSC-SEG enrichments across the rest of SNPs (Supplementary Data p = 0.029) and neuronal cell-type (FDR-p = 0.017), schizophrenia predisposing variation within RNS markers was found to be enriched beyond brain-related tissues and not enriched in any brain-related cell types  and not harboring (468 genes) RNS markers were tested for functional over-representation analysis (ORA) using the whole gene-set as background. Although no brain-relevant overrepresentation was found in any case, we observed an enrichment of loci subject to RNS in brain unrelated functional signatures  and that the derived alleles confer protection rather than risk to schizophrenia. Thus, our results are in line with recent studies reporting negative selection of schizophrenia predisposing alleles61. Pardiñas et al.26 have suggested a plausible explanation of the purported schizophrenia evolutionary paradox of persistent common variation and progressive removal of risk alleles through background selection62. By this mechanism, removal of rare haplotypes harboring deleterious mutations could reduce genetic diversity and allow common alleles with small deleterious effects to maintain a high frequency by drift62.Previous studies have tried to explain why genetic predisposing variation to schizophrenia persists in the population, despite the reproductive fitness reduction in affected individuals33, a reliable explanation for the persistence of common alleles conferring risk to schizophrenia may reside on fitness advantages provided during earlier stages of the human evolution. In this sense, a previous study focusing on the Sapiens-Neanderthal divergence described a pattern of positive selection of schizophrenia predisposing variation that could have contributed to the Homo sapiens success against other human species41. Moreover, schizophrenia loci were also described to be enriched in genomic regions that had experienced specific evolutionary acceleration during early human evolution (HARs) in comparison with other non-human primates63. Although these evidences reinforce the idea of schizophrenia predisposing variation acquisition as a price to pay for human abilities such as language development24 or even more adaptive immunological profiles64, the evolutionary pressures to retain schizophrenia risk alleles as an evolutionary advantage might have stopped acting before the dispersion of the Homo sapiens from Africa. In line with our results, studies exploring RNS patterns have not found a pattern of positive selection of schizophrenia predisposing alleles29. A recent study has proposed an evolutionary framework by which schizophrenia risk alleles increased their frequency with the development of the social brain and high-order cognitive functions, but after a turning point the trend was reversed and a negative pressure against schizophrenia alleles became the standard61. Interestingly, this turning point from positive to negative selection of predisposing alleles in schizophrenia could be shared by other psychiatric traits. In fact, a recent work observed a similar scenario for attention-deficit/hyperactivity disorder (ADHD): while introgressed Neanderthal alleles were enriched in ADHD risk variants, modern environments triggered the progressive elimination of ADHD-predisposing alleles65. This temporal perspective should also prevent readers from reaching conclusions from current evolutionary dynamics. While our approach explored RNS from around 100,000 years ago, recent methods have been used to assess modern selection from up to 100 generations (around 2000 years ago)67. In these recent studies, schizophrenia was also affected by even more recent negative selection67.Apparent contradictory results regarding the positive or negative selection of alleles that predispose to schizophrenia need to be integrated using a dynamic perspective. Since our study has focused only on genetic selection initiated after African populations started their dispersion into Eurasia around 60,000–100,000 years agoloci.Given the evidence here described about the relationship between predisposing variation to schizophrenia and RNS throughout human populations, we assessed whether these evolutionary dynamics were also present at the Asian or European intrapopulation level. While the association between RNS and the genetic predisposition to schizophrenia is replicated in European populations, this association appears to be absent among East Asian populations. This finding suggests that the observed relationship between schizophrenia and recent natural selection may be driven by selective pressures resulting from other traits, acting through specific environments that are unique to certain populations. However, the considerably smaller sample size of the Asian schizophrenia cohorts compared to the European samples could be the main cause of the lack of association between recent natural selection and schizophrenia predisposing loci subject to RNS, as compared to those not subject to RNS. While common schizophrenia predisposing variation not subject to RNS exhibit clear patterns of heritability enrichment in brain-related tissues and neuronal cell types, aligning with expectations from prior studies, schizophrenia predisposing variation under RNS display lower enrichments in neuronal and brain-related functions, along with significant heritability enrichments in other tissues not directly linked to the central nervous system, such as the kidney or liver  within the SLC39A8 gene has been described to be under positive selection of its derived risk T allele in Europeans39. This evolutionary event, however, has been reported to be driven by the migration of modern humans out of Africa and the consequent adaptation to colder climates by reducing blood pressure and the risk for hypertension40. Similarly, survival of the derived risk T allele of variant rs1150711 (C/T) of the ZNF323 gene could be the result from the ameliorated lung function provided by this allele to European populations59. These and similar examples of antagonistic pleiotropy, in which the allele that predisposes to schizophrenia confers adaptive advantage or protects against another condition, have been used to explain the evolutionary paradox of schizophrenia. However, our study suggests that, on a genome-wide scale, non-antagonistic pleiotropy could be contributing to the RNS enrichment across schizophrenia common variation. In this sense, recent positive selection of schizophrenia derived protective alleles could also be a likely by-product of the pleiotropic effect of some genetic variants favoring adaptation to the environment during modern evolution of human populations69.In fact, our results pointing to pleiotropic effects of schizophrenia 29 could therefore be the result of distinct evolutionary pressures related to other phenotypes, with predisposing variants having also an impact on schizophrenia risk. Although most of schizophrenia alleles have been described to exert similar effects across populations70, allele frequencies could vary across populations, thus leading to differences in individual genetic risk profiles. In this sense, greater polygenic scores for schizophrenia have been described in African populations71. However, reportedly greater polygenic scores and our finding of positive selection of schizophrenia derived protective alleles do not imply that African populations are at higher genetic risk for schizophrenia. Since GWAS have been performed mainly in cohorts of European ancestry, there is a limited portability for the estimation of polygenic risk scores across African cohorts using the available GWAS data71, and these inferences should be avoided.Differing genetic risks for schizophrenia described across distinct populations55. Consequently, the predictive performance of a set of variants will decrease as the level of pleiotropy increases. If there is an excess of pleiotropic variants among the RNS derived protective alleles compared with derived risk alleles, this might explain the higher predictive capacity of a PGS based on derived risk alleles.By evaluating the PGS predictions on schizophrenia within RNS with derived protective and risk alleles separately, we observed greater variance explained across similar numbers of risk than protective RNS markers Fig. D. These 49). In this sense, however, our sensitivity analyses considering population specific data lead to similar results in the case of European population, and therefore validating our findings, although this scenario was not replicated in East Asian populations. Therefore, the implications of our results suggesting protective selection by non-antagonistic pleiotropy may be limited, since environments shaping this evolutionary pattern could be absent in other populations. Nevertheless, this inconsistency between European and East Asian population specific analyses may be caused by a great difference in statistical power, and larger Asian cohorts should be used to rule out this possibility. Second, to have sufficient statistical power, our analysis is restricted to variants having a MAF higher than 5%. This filter could have removed many GWAS signals with remarkable RNS effects. For instance, a variant within SLC39A8, a schizophrenia-associated gene with well-described evolutionary properties, is absent from this study due to its low allele frequency. Third, along the lines of a previous related study72, we have used the top 5% markers with the highest probability of being subject to RNS for our main analyses in order to have enough statistical power. Finally, it is worth noting that while pcadapt has been employed in previous studies involving similar 1000 Genomes data47, PCA-based methods have been reported to have a susceptibility to false positives when applied to populations with pronounced stratification and a non-continuous principal component space. In this regard, the concurrence of selection outliers detected by alternative Fst methods served as validation for our identification of RNS markers using pcadapt.This study was subject to several limitations. First, we described RNS markers using whole 1000 Genomes data, while we used association data from mainly European-ancestry schizophrenia cohorts , we performed scans detection of RNS signatures using a principle components-based approach implemented in 73, across African, European, and Asiatic populations. American populations, who show greater genetic heterogeneity due to recent admixture events, were eliminated from the analysis, as suggested by the Pcadapt developers47. Moreover, given the elevated inbreeding coefficients for some of the 10,000 Genomes subpopulations74, only 1699 subjects that have been previously described as outbred and unrelated74 were finally considered. We retained common genetic variation (MAF > 0.05), biallelic, and overlapping with summary data from the schizophrenia GWAS used in this study, thus yielding a total of 5,554,437 SNPs.To study RNS signatures we used genetic data from the 1000 Genomes phase 3 sequencing database75, Pcadapt accounts for LD-genome structure  for the estimation of RNS probabilities for each of the 5,554,437 SNPs considered. The distribution of PC loadings was evaluated to ensure that selection signals correspond to regions subject to adaptation rather than to regions of lower recombination (high LD). We used Cattell’s rule to select the appropriate number of PCs (K = 3). Pcadapt test was then performed and derived p-values (pRNS) for every SNP were calculated to inform about their likelihood of being subject to RNS.Since LD can affect ascertainment of population structurepRNS; RNS markers) after LD-clumping based on schizophrenia GWAS p-values (PLINK v1.9 parameters-clump-r2 0.1-clump-kb 500) and refer to them as RNS markers. We prioritized the association with schizophrenia and the top 5% RNS markers were selected to have enough SNPs with which to perform the subsequent analyses. However, to ensure that the reported results were not biased by LD-clumping based on SCZ p-values, we also considered the top 5% RNS markers after LD-clumping based on pRNS and refer to them as LD-RNS markers.Throughout the subsequent analyses of the study, we consider the top 5% selected markers . Main analyses were performed using the whole summary statistics . Moreover, both ancestry-specific summary statistics for European  and East Asian subjects  were used for additional sensitivity analyses to explore association between RNS signals within European or East Asian populations and ancestry-specific predisposing variation to schizophrenia. As a specificity analysis for the detection of selection signals, we also used Alzheimer’s disease51 GWAS summary statistics in independent analyses. This disorder was selected based on its adequate statistical power comparable to that of schizophrenia, its described clinical similarities, and its later age at onset, after natural selection pressure has exerted its effect. Details regarding the summary statistics used are described in Supplementary data We used the latest summary statistics of the schizophrenia GWAS (PGC-SCZ3) conducted by the Psychiatric Genomics Consortium (PGC)Pcadapt in the analysis. 6,693,073 variants were used in the case of Alzheimer’s disease.The Major Histocompatibility Complex (MHC) region was excluded in all analyses and only biallelic SNP and those with an imputation quality score > 0.9 were considered. Overall, 5,554,437 variants from 1000 Genomes overlapping with schizophrenia summary data were converted to PLINK format and used as the input for 39. There is no overlap between PGC-SCZ2 and SCZ_CIBERSAM samples.We used a case–control sample including 1927 schizophrenia cases  and 1561 healthy controls (HC)  from CIBERSAM  as an independent target sample for PGS predictions (SCZ_CIBERSAM). All research was performed in accordance with relevant guidelines/regulations. Informed consent was obtained from all individual participants included in the study, and ethic boards/committees from the following involved Spanish hospitals approved the protocol: Clinical Research Ethics Committee of the Hospital Sant Joan de Reus, Research Ethics Committee of Asturias, Research Ethics Committee of Cantabria, Bioethics Commission of the University of Barcelona (CBUB), Galician Regional Research Ethics Committee, Scientific Research Ethics Committee of Hospital Gregorio Marañón and Research Ethics Committee of the Valencia’s clinical Hospital. All participants were genotyped as part of the Psychiatric Genomics Consortium (PGC), and passed quality control (QC filters) per PGC-SCZ2 criteriaSCZ) were calculated from PGC-SZ239 GWAS summary statistics as discovery sample and SCZ_CIBERSAM case–control cohort as target sample. Summary data from the latest schizophrenia GWAS49 was not used to estimate PGS because target sample was included as part the cohorts in the study. PGSSCZ were calculated using SNPs present in the 1000 genomes database for the studied populations. We included only biallelic variation, with imputation quality scores > 0.9, and excluded indels. 65PLINK 1.9 was used to calculate PGS across schizophrenia patients and healthy controls weighted by the logOR in the discovery sample. Standardized PGS were calculated, and significance was evaluated by logistic regression, using case–control status as dependent variable and sex, age, and the first 10 MDS ancestry components as covariates. We calculated explained variance attributable to PGS as the increase in Nagelkerke’s pseudo-R2 between a model with and without PGS variable.PGS for schizophrenia  and the whole genome variation to estimate predictions in the SCZ_CIBERSAM case–control cohort. The most significant P threshold (P < 0.2) was selected for the subsequent PGS analyses stratified by RNS. We then performed stratified PGS predictions to compare SNPs that were subject to RNS to those that were not. Summary SNP data with PSCZ < 0.2 was divided into 20 quantiles of increasing pRNS. PGS predictions were performed across the 20 SNP quantiles in the CIBERSAM case–control sample. Linear regression was performed to evaluate the change in the variance explained by PGS on case–control status in the CIBERSAM sample across the 20 quantiles. Nagelkerke’s pseudo-R2 from PGS predictions using the first quantile, corresponding to the 5% of SNPs with the highest probability of being subject to RNS, was compared against the distribution of pseudo-R2 obtained by selecting the same number of SNPs from the remaining 95% of SNPs. On account of the likely bias in prediction due to the non-random genome features of SNPs subject to RNS, selection of SNPs from the remaining 95% was carried out by identification of sets of randomly drawn SNPs that were matched to the top 5% selected SNP based on allele frequency, number of SNPs in LD, distance to nearest gene, and gene density using default parameters from SNPsnap77 (https://data.broadinstitute.org/mpg/snpsnap/). Since an earlier study by Price et al. suggested that recent selection signals could be partly explained as artifacts caused by long-range LD regions53 that can lead to inflated variance explanations from variants subject to RNS, we repeat the previously explained stratified PGS predictions after removing 24 described Long-Range LD Regions as a sensitivity analysis to assess whether the results hold.Initially, we used several P thresholds (SCZ < 1) or risk (derived-ORSCZ > 1) to schizophrenia. Across variants subject (RNS markers) and non-subject to RNS, independently, we compared 1000 predictions from protective and risk variants, using a similar number of SNPs (NSNPs = 1000), on the SCZ_CIBERSAM case–control sample. Wilcoxon test was used to compare the pseudo-R2 distributions of predictions for SNPs with a protective (derived-ORSCZ < 1) or risk (derived-ORSCZ > 1) derived allele across SNPs subject (RNS markers) and non-subject to RNS.Additionally, we also calculated stratified PGS after subsetting SNP summary data into those for which the derived allele that emerged during human evolution conferred protection (derived-ORh2SNP) estimates for the resulting genome partitions after dissections of schizophrenia summary genetic data based on RNS markers following the recommended procedure57 (https://github.com/bulik/ldsc/wiki/Partitioned-Heritability).We calculated SNP-based heritability (i)49 that belong to the top 5% with the highest likelihood (lowest pRNS) of being a RNS marker) and the rest of the SNPs (the remaining 95% of the SNPs from schizophrenia GWAS summary data).RNS markers (SNPs from schizophrenia GWAS (PGC-SCZ3) summary statisticsii)56, 13 brain-related tissues (Brain GTEx57), and 3 brain cell-type annotation files .Sub-annotations from the intersection between the described annotations (RNS markers and the rest of SNPs) and gene expression data from 10 whole tissuesFirst, we created per SNP annotation files (one per chromosome and desired annotation). Each file consisted of a row per SNP and a column for each sub-annotation . Annotation files were created for:ldsc v1.0.157, a command line tool for estimating heritability. We performed both heritability enrichment analyses across the described annotations (–h2) and one-sided t-tests to evaluate whether the cell-type enrichment in schizophrenia within a particular annotation was higher than the same cell-type enrichment in schizophrenia outside the target annotation (anti-target) but within a background annotation (using –h2-cts). Control background annotations from the original study were used57.We used 73. LD scores were computed for each annotation file using the recommended parameters: 1-cM window (–ld-wind-cm 1), restriction to Hapmap3 SNPs, and exclusion of the MHC region due to its high gene density and exceptional LD, as recommended by the developers15. The ‘–overlap-annot’ argument and 1000 Genomes phase 3—based frequency files (‘1000G_Phase3_frq’ files via –frqfile-chr argument) and LD weights (‘weights_hm3_no_hla’ files via-w-ld-chr argument) were used for LD score calculations.We ran LDSC using associated data files from phase 3 of the 1000 Genomes Projecthttps://data.broadinstitute.org/alkesgroup/LDSCORE/), as independent LD scores.Partitioned LDSC computes the proportion of SNP heritability associated with each annotation column while considering all the remaining annotations. This is performed by regression models using the estimated LD-scores jointly with other independent LD scores for baseline annotations to improve the model performance. We used the full baseline model v2.2, consistent of a full annotation column  and 158 independent functional annotations, available at LDSC repository  that contained at least one credible SNP from 249 regions with low numbers of expected causal SNPs (K < 3.5) were used49. Genes mapped only from RNS markers (22 genes) were compared against genes mapped by SNPs not subject to RNS (468 genes).We used FINEMAP results of the schizophrenia GWS http://www.webgestalt.org/)78. All mapped genes from schizophrenia GWS loci studied here in this study were used as a background list. Enrichment across gene sets from Gene Ontology (GO) cellular components (CC) and biological functions (BF) categories was evaluated. FDR by Benjamini–Hocheberg adjustment was used to evaluate enrichment significance across GO gene sets, and a minimum threshold of 5 genes overlapping with each gene set was considered.Functional overrepresentation of genes from each category was assessed by over-representation analysis (ORA) with WEB-based GEne SeT AnaLysis Toolkit . One-sample Kolmogorov–Smirnov test was performed to evaluate the overrepresentation of SNPs subject to RNS after principal components-based approach implemented in Pcadapt. Fisher’s exact tests were performed to study the enrichment for the RNS markers  or the LD-RNS markers  across the different schizophrenia GWAS thresholds . We also analyzed enrichment for the RNS markers for Alzheimer’s disease (NSNPs = 6263). Spearman correlation between P values from GWAS and RNS was performed . Correlations were confirmed by conducting 10,000 random permutations of the GWAS results with respect to the pRNS values and testing whether the observed correlation coefficients were significantly higher than the ones in the null distribution of the permuted datasets.Statistical analyses were performed using R  for each SNP and evaluated the overrepresentation of protective or derived risk alleles across schizophrenia GWAS thresholds: chi-square tests were performed to compare the proportion of derived risk alleles (derived-ORSCZ > 1) within and outside RNS markers (top 5% RNS loci) across schizophrenia GWAS thresholds . Additionally, one sample t-tests were performed to compare the average derived-ORSCZ within and outside RNS markers (top 5% RNS loci) to the neutrality across schizophrenia GWAS thresholds . Two sample t-tests were also performed to compare derived-ORSCZ within vs outside RNS markers.We calculated GWAS derived-ORloci subject to RNS with the derived protective or risk allele having the lead association with schizophrenia among all phenotypes included in GWAS Atlas (https://atlas.ctglab.nl/)79.We used Fisher's exact tests to evaluate the enrichment of schizophrenia GWS Supplementary Figures.Supplementary Information 1.


Major aortic branches are routinely included in simulations but minor branches are virtually always neglected, despite being implicated in TBAD progression and the development of complications. As minor branches are estimated to carry about 7–21% of cardiac output, neglecting them may affect simulation accuracy. We present the first simulation of TBAD with all pairs of intercostal, subcostal and lumbar arteries, using 4D-flow MRI (4DMR) to inform patient-specific boundary conditions. Compared to an equivalent case without minor branches, their inclusion improved agreement with 4DMR velocities, reduced time-averaged WSS (TAWSS) and transmural pressure and elevated oscillatory shear in regions where FL dilatation and calcification were observed in vivo. Minor branch inclusion resulted in differences of 60-75% in these metrics of potential clinical relevance, indicating a need to account for minor branch flow loss if simulation accuracy is sought.Type-B aortic dissection (TBAD) is a disease in which a tear develops in the intimal layer of the descending aorta forming a true lumen and false lumen (FL). Because disease outcomes are thought to be influenced by haemodynamic quantities such as pressure and wall shear stress (WSS), their analysis The online version of this article contains supplementary material which is available 10.1007/s10439-023-03175-4. Surgical interventions such as thoracic endovascular aortic repair (TEVAR) are deployed in the presence of complications, including ischemic conditions, to encourage total FL thrombosis and promote favourable aortic remodelling .32Aortic dissection (AD) is a life-threatening condition in which a tear forms in the innermost layer of the aorta, separating the true lumen (TL) from a false lumen (FL) as blood flows between the layers of the aortic wall. Type-B AD (TBAD) is characterised by a primary entry tear (PET) in the descending aorta. Uncomplicated cases of TBAD can be treated medically, but the disease is dynamic in nature; FL dilatation36 helical and rotational flow,15 and FL pressure40 in the onset and progression of AD. Haemodynamic analysis may therefore offer predictive capabilities to support clinical decision-making. Computational fluid dynamics (CFD) and 4D-flow MRI (4DMR) are two prevalent analysis modalities. While the accuracy of CFD simulations relies heavily on modelling assumptions such as the patient-specificity of boundary conditions,2 4DMR is limited in spatio-temporal resolution (12) and is subject to imaging errors that result in substantial uncertainties in flow rate measurement,24 WSS39 and velocity.12 Informing and validating CFD with 4DMR data offers a favourable compromise between accuracy and resolution, especially where small-scale anatomical features like dissection tears are of interest.A growing body of evidence implicates haemodynamic quantities such as wall shear stress (WSS),25 and aneurysmal development26 in AD. Although patient-specific simulations with all major branches are routine, studies including minor aortic branches such as the segmental arteries remain scarce. The segmental branches include the intercostal, subcostal and lumbar arteries, which branch from the dorsal descending thoracic and abdominal aorta in pairs. These small (1–4.2 mm diameter23) but numerous vessels form part of an extensive collateral network of vessels supplying the spinal cord and other vital tissues and have been reported to accept between 7 and 21% of cardiac output (CO) in healthy subjects.30The number of vessels branching from the FL has been significantly associated with failed FL regression29 Conversely, segmental patency has been indicated as a significant protective factor in TBAD.29 To complicate matters, occlusion or removal of the segmental arteries during endovascular or surgical treatments for TBAD is currently attributed as the cause of postoperative paraplegia due to spinal cord ischemia (SCI).37The segmental branches play a complex role in TBAD. Independently of other FL branching vessels, their patency has been associated with negative outcomes including aneurysmal development.19 but without haemodynamic assessment. The inferior mesenteric artery (IMA) and a selection of FL-branching intercostal arteries were recently included in a TBAD simulation.3 However, TL branches were excluded and boundary conditions were not patient-specific, which has introduced large simulation errors in previous studies of TBAD.2 To the authors’ knowledge, no patient-specific CFD simulations of human aortae with segmental arteries have been reported to date.To date, minor branches have virtually always been neglected in simulations of the aorta due to limitations in medical image resolution, computational power, and a lack of available research on appropriate boundary conditions. Segmental arteries have been included as structural supports in aortic fluid–structure interaction (FSI) studiesThe inclusion of minor branches and their flow loss will likely affect WSS and pressure distributions in simulations of TBAD. The magnitude of this effect may have implications for using haemodynamic markers to aid clinical decisions. In this study, we report a technique that simulates all pairs of segmental arteries in a patient-specific TBAD case. We evaluate their haemodynamic impact by comparing simulations with and without them, using 4DMR data and brachial pressure measurements to inform a patient-specific three-dimensional, three-component inlet velocity profile and three-element Windkessel outlet boundary conditions.Computed tomography angiography (CTA) data from a 56-year-old male patient with chronic TBAD were acquired using a Siemens SOMATOM Definition Flash  with an isotropic spatial resolution of 0.5 mm. A 3D rendering of this CTA data is shown in Fig. mentclass2pt{minimThe dissection begins at the bifurcation of the left subclavian artery with a large PET mentclass2pt{minimmentclass2pt{minimmentclass2pt{minimD, as shown in Fig. The computational domain was segmented from CTA data and non-rigidly registered onto the thoracic 4DMR domain from the data acquired four months later. CTA data was used for the initial segmentation due to its superior resolution, while the registration was performed so that the overall aortic shape matched that observed in the 4DMR data during validation; the position of the patient in the scanner can greatly change the shape and hence the flow distribution within the aorta. Any FL dilatation during the 4 months between CT and 4DMR scans was reconciled during non-rigid registration. The full extent of the dissection and all major branches were included. Two otherwise identical domains were then produced: one with minor branches, entclass1pt{minima10 to determine the appropriate mesh sizing, as described in Supplementary Material SM2. The final meshes for D and Unstructured tetrahedral volume meshes were generated using Fluent Mesh . A mesh independence study was carried out using grid convergence index (GCI)Three-component velocity data was extracted from the thoracic 4DMR data on the same plane as the CFD inlet to apply a patient-specific three-dimensional, three-component inlet velocity profile. As the inlet plane moves in space and time due to aortic compliance and heart movement, an algorithm was developed in MATLAB  to dynamically map the 4DMR inlet onto the static CFD inlet, and to interpolate the 4DMR data in time to match the CFD timestep. Spatial interpolation of the inlet data onto the CFD mesh was performed by the CFD solver, ANSYS CFX 2020 R2 .in vivo, so without knowledge of patient-specific individual minor branch flow rates, applying a common pressure outlet condition in groups may make more physiological sense than constraining the individual flows.Three-element Windkessel (WK3) outlet boundary conditions were applied to reconstruct physiological and patient-specific flow and pressure conditions in the aorta. Rather than using individual WK3s at every minor branch outlet, they were grouped based on location and connected jointly to a single WK3, as shown schematically in Fig. The 7 intercostals in S1 all branch from the FL while the 11 S2 intercostals all branch from the TL. S3 consists of a single pair of subcostal arteries bifurcating from the FL. S4 comprises four pairs of lumbar arteries that also bifurcate from the FL and the IMA, originating from the TL, was provided with its own WK3 outlet.B to tune patient-specific WK3 parameters. Mean measured flow rates, A target mean flow rate 23 to derive b. See Supplementary Material SM4 for further details. All target outlet flow rates, Since the minor branches are smaller than the resolution of 4DMR, and their flow loss is of a similar order to 4DMR uncertainty, we used Doppler ultrasound measurements of the individual segmentals and the IMA from healthy subjectsmentclass2pt{minim35. Pressure targets and measurements, and their simulated values, are shown in Table Finally, target systolic and diastolic pressures, entclass1pt{minimavia a lumped parameter model of the aorta using our previously developed technique.31With target inlet pressure and mean outlet flow rates determined, WK3 parameters were tuned 31The three-dimensional incompressible Navier–Stokes and continuity equations were solved numerically using the finite-volume solver ANSYS CFX 2020 R2. Walls were assumed to be rigid, both for computational efficiency and due to a lack of Cine-MRI data to tune patient-specific aortic compliance with our existing techniques.et al.33 and a density of 1056 kg/mRe) for pulsatile cardiovascular flow,28 the nominal shear rate,9 and the peak inlet velocity from 4DMR, a peak 2822 The use of RANS models is open to question in the context of pulsatile blood flow, even with transition to turbulence. An equivalent set of laminar flow simulations were carried out to ensure that the study conclusions were upheld. This analysis can be found in Supplementary Material SM3.Blood was modelled as a non-Newtonian fluid using the Carreau–Yasuda viscosity model with empirical constants from Tomaiuolo Transient simulations with timesteps of 1 ms were solved using the implicit, second-order backward-Euler method using a root-mean-square residual value of D and Flow rate, pressure, velocity magnitude and WSS indices were analysed in each simulation to compare haemodynamics in cases Q, was extracted from CFD and 4DMR on selected analysis planes throughout the dissection. On a given plane Q was defined at each timestep as:A is the cell/voxel area. Next, Q was decomposed into forward and reverse flow rates to assess the degree of retrograde flow in the FL, which may be linked with TBAD progression.14 At any given timestep, forward and reverse flow regions R/F and t is the start time of the final cycle and T is the cycle period. FL ejection fraction (FLEF), a predictor of aortic growth rate,8 was also assessed by evaluating The net instantaneous flow rate, D and 38 provides a quantification of luminal interaction and is defined as:To compare pressure distributions between 21To assess the impact of minor branches on WSS distributions, time averaged WSS (TAWSS), oscillatory shear index (OSI), and endothelial cell activation potential (ECAP) were computed using every fifth timestep (every 5 ms) of the final cycle as follows:D and Simulated mentclass2pt{minim23 It is important to note that 4DMR suffers from numerous sources of uncertainty. Poor accuracy is observed in low-velocity regions due to a low signal-to-noise ratio.24 Depending on spatial resolution and the choice of VENC, 4DMR is also prone to underestimating peak velocity34 and overestimating luminal diameter.12 As a result, uncertainties in velocity and flow rate of 20–110% have been reported in single-VENC 4DMR in healthy ascending aortae.24 In this study, measurement uncertainty in 4DMR data was not readily quantifiable. Additionally, the magnitude and source of measurement errors differ in each lumen due to their relatively different sizes and velocity ranges. For these reasons, we use the total plane flow rate in Fig. Minor branch outflow caused a progressive reduction in the total flow rate along the aorta, leading Including minor branches reduced net flow through the PET by 7.9%, drawing more flow into the TL. A progressive delay in peak flow rate is observed in the 4DMR data in Fig. Examining forward and reverse flow dynamics in the FL, the evolution of Observing the temporal dynamics of forward and reverse flow on plane d in Fig. Figure D. This indicates that the first balance point (FBP), defined as the first location where d is also the only location where TMPD and Plane d on Fig. D and Velocity magnitude contours from simulations and 4DMR are compared on selected planes at peak systole . We have assessed their haemodynamic impact in a patient-specific simulation of uncomplicated chronic TBAD exhibiting long-term FL dilatation. Minor branch flow loss reduced velocity magnitude along the dissection, providing favourable agreement with 4DMR data. Neglecting this loss increased TAWSS by up to 70% and TMP by 61%. Minor branch flow loss also increased ECAP by up to 75%, notably in regions where aneurysmal dilatation and calcification were observed 3 has investigated the haemodynamic impact of minor branches in TBAD, though without patient-specific boundary conditions and only including branches originating from the FL. They applied a 5% flow loss through 11 intercostal vessels and 2.2% through the IMA using fixed flow rate outlets, observing increased TAWSS around minor branch bifurcations, a 1 mmHg reduction in TMP magnitude and a reduction in TL velocity in the distal thoracic aorta, in agreement with the current study. Contrary to our findings, they observed a 2% increase in PET flow. This was attributed to the low-pressure minor branch outlets in the FL drawing additional flow through the FL. Because our study also includes TL branches, which outnumber FL branches in the thoracic aorta and carry 46% more flow, the opposite effect was observed: a 7.9% reduction in PET flow. Thus the inclusion of all minor branches, and the flow loss applied to them, appear to be an important consideration for accurate luminal flow distributions in simulations of TBAD.To our knowledge, this study represents the first analysis of the effect of minor branches on aortic haemodynamics using patient-specific boundary conditions. Only one other study,38 However, pressure dynamics differed between cases in the proximal thoracic FL where substantial aortic growth was observed. The greater number of TL minor branches and thus their greater outflow caused FL pressure to dominate TL pressure more proximally in 38 Despite equal systolic and diastolic pressure at the inlet, neglecting minor branch flow loss increased mean and peak TMP magnitude by With or without minor branches, 42 Despite substantial aneurysmal growth in this patient, a low-to-moderate degree of reverse flow and negligible FLEF  between TL and FL in this patient which act to minimise flow and pressure gradients between them. As a result, minor branch flow loss does not greatly affect reverse flow and Mean reverse/forward flow ratio, 20 Minor branch flow loss progressively reduced TAWSS was along the aorta, up to 70% in the iliac branches. High TAWSS around luminal tears, such as at point 11 so a reduction of this magnitude may affect the prognostic value of simulations if they are incorporated into future clinical processes. In addition, OSI and ECAP were elevated with the inclusion of minor branches, with ECAP increasing by up to 75% at Low TAWSS and high OSI have also been linked with aneurysmal growth, both of which are observed throughout the thoracic FL of this patient.12 Minor branches progressively reduced the total plane flow rate and peak velocity in both lumens, leading to a favourable agreement with 4DMR overall. However, uncertainty in 4DMR velocity and flow rate may therefore be particularly high in this case (and other cases of AD) due to widespread regions of very low velocity and small luminal area compared to a healthy ascending aorta. We indeed observe greater discrepancies between CFD and 4DMR in the distal regions, though these were substantially reduced when minor branches were included.Both simulations achieved excellent qualitative agreement in velocity magnitude distributions with 4DMR. CFD predicted higher mean velocity than 4DMR at all planes, an effect commonly observed in comparisons between CFD and 4DMR.Taking measurement errors into consideration, we cannot make firm conclusions on the relative accuracy of each CFD simulation using 4DMR data alone. However, we have reasonably assumed that minor branch flow loss is within the healthy physiological range in this patient due to the patency of the minor branches in CTA data and their lack of ischemic conditions. Based on these assumptions and the improved velocity agreement in 24 However, a systematic offset in velocity does not affect our conclusions. Due to 4DMR imaging errors, the inlet velocity profile may exhibit weak velocity divergence, contravening the incompressibility assumption. In our simulations, the pressure coupling algorithm will locally redirect flow in the cells immediately neighbouring the inlet to preserve continuity. No issues in convergence and numerical stability were observed throughout this study, indicating that any such effects were minimal. Furthermore, any non-physiological impact will affect both cases equally and would not change our conclusions. Errors in target flow rate at the major outlets may also result from 4DMR uncertainties, and from using 4DMR data acquired two years later at the iliac branches. As equivalent boundary conditions were applied in each simulation, this also does not affect our conclusions. Although minor branch flow rates were consistent with literature values, simulated WSS and velocity distributions within them exceeded the physiological range. This either indicates insufficient branch diameter, or measurement errors in the Doppler ultrasound data.23 Furthermore, we have assumed constant minor branch diameter, but branches near the Adamkiewicz artery  and vessels on the patient’s left side are typically larger and carry more flow.23 This again does not affect our general conclusions as we have only endeavoured to explore the global impact of minor branch flow loss on WSS distributions in the major branches and aortic lumina.Various limitations and sources of simulation should be mentioned. 4DMR may underestimate flow rate and stroke volume by 41 However, the magnitude of these differences increased with flap compliance which is likely to be low due to the chronicity of this case of TBAD. Furthermore, time shifts in TL and FL pressure waves tend to zero in cases where large or numerous luminal communications are present; the assumption of a rigid flap has been previously justified on this basis.7 Even where flap compliance is large, TMP is minimally affected.41 Finally, we have used a RANS turbulence model for computational efficiency which may affect the accuracy of WSS distributions1; however, comparisons with equivalent laminar flow simulations  provided identical conclusions to those presented here.In terms of modelling assumptions, walls were assumed to be rigid. Compared with compliant simulations, the assumption of a rigid wall in TBAD has been shown to reduce peak TAWSS, expand regions of high oscillatory shear and low TAWSS, and affect the distribution of flow through luminal tears.This study represents an initial exploration of the impact of minor branches in a single case of TBAD Below is the link to the electronic supplementary material.


GW approximation and the Bethe–Salpeter equation.We find that the quasiparticle band structures, linear absorptionspectra, and exciton binding energies depend strongly on the distanceand the alignment of adjacent metal halide perovskite layers. Furthermore,we show that exciton delocalization can be modulated by tuning theinterlayer distance and alignment, both parameters determined by thechemical composition and size of the organic cations. Our calculationsestablish the general intuition needed to engineer excitonic propertiesin novel halide perovskite nanostructures.Layered organic–inorganic halide perovskites exhibitremarkablestructural and chemical diversity and hold great promise for optoelectronicdevices. In these materials, excitons are thought to be strongly confinedwithin the inorganic metal halide layers with interlayer couplinggenerally suppressed by the organic cations. Here, we present an in-depthstudy of the energy and spatial distribution of the lowest-energyexcitons in layered organic–inorganic halide perovskites fromfirst-principles many-body perturbation theory, within the  While they are formallybulk three-dimensional (3D) materials, the alternation of inorganicand organic layers is thought to lead to a quasi-two-dimensional behaviorof electronic and optical properties.13 Interlayerelectronic coupling and charge transfer are suppressed,16 and photoexcited electron–hole pairs (excitons) are stronglybound and localized within the inorganic layer, as a consequence ofquantum confinement.19 Signatures of electron–phonon and exciton–phononcoupling are observed in photoluminescence spectra of layered perovskitesthat exhibit regularly spaced peaks.21 These stronginteractions also likely give rise to the formation of self-trappedexcitons, which have been attributed to broad photoluminescence spectraand white light emission in layered halide perovskites.1 Furthermore, recent experimental measurementsreport possible evidence of interlayer exciton transport,22 interlayer exciton delocalization,23 or charge transfer excitons24 in bulk layered perovskite systems, which may be exploredin devices.26 These studies highlight the need for a systematic understandingof how the localization of excitons in layered organic–inorganichalide perovskites can be tuned through the exploration of the broadchemical and structural heterogeneity of this family of materials.Layered organic–inorganichalide perovskites make up a structurally and chemically heterogeneousfamily27 It is also typically associated with a typeII energy band alignment in a heterostructure29 and/or withspin-valley locking occurring as a result of broken inversion symmetry.30 For example, low-dimensional van der Waals boundsystems, including those based on transition metal dichalcogenides(TMDCs), are known to facilitate formation of long-lived excitonsthat delocalize across different layers, such as dipolar and quadrupolarinterlayer excitons reported in hetero bi- and trilayers of TMDCs;32 these properties can also betuned, for example, by twisting constituent layers.34 Furthermore, formation of interlayer excitonshas also been reported in bulk MoTe2.30 While engineering type II band alignments in heterostructures,including layered perovskites, has become increasingly possible, thanksto the rapid development of scalable synthesis techniques,36 it is not clear how interlayer electronic coupling might be achievedin these systems given that the organic molecules can separate metalhalide layers sometimes by very large distances (on the order of nanometers).37 Therefore, a microscopic understanding of theextent to which excitons might be able to delocalize across layersin bulk layered organic–inorganic perovskites is required,and first-principles calculations play a key role in this context.In this Letter, we start to develop this understanding through a detailedfirst-principles study of the spatial delocalization of excitons inbulk layered perovskites.Correlation of photoexcited electron–hole pairs which arelocalized in spatially separated layers can be facilitated by thecoupling of single-particle wave functions from neighboring layers.GW approximation38 and the Bethe–Salpeter equation40 (GW+BSE) are state-of-the-art methodological frameworksfor computing the excited state properties of semiconductors and insulatorsand have been applied successfully to understand the photophysicsof heterogeneous systems, including TMDCs42 and metal halide perovskites.48 Spatial delocalization of excitons has been revealed in complexmaterials systems such as the bulk30 andheterostructures33 of TMDCs by visualizingthe two-particle exciton wave function computed as a solution of theBSE. Furthermore, the computed exciton wave function can be used toestimate the average electron–hole separation correspondingto a particular excited state and to quantitatively assess the realspace extent of the exciton wave function, as was shown, for example,in organic semiconductors.50 Because of the structuraland chemical complexity of organic–inorganic layered halideperovskites, only a few first-principles studies of optical excitationshave been reported in the literature for these systems,52 which focus on computing the quasiparticle band structure and opticalabsorption spectra.The GW+BSE, we rationalizethe physical mechanism for interlayer delocalization of excitons tobe based on the orbital decomposition of band edge states. Our studyfocuses specifically on lead iodide layered perovskites with planarinorganic layers that are one octahedron thick  and the alignment between two adjacent layers,  and compute their electronic structure within density functional theory(DFT)54 and the GW approximation56 . Such model systems have been successfullyused by us and others58 to capture the main trends in the photophysicsof layered perovskites at a reduced computational cost. The bottomleft and top right corners of the map shown in 59 with alignment  and the Ruddlesden–Popper (RP) phase62 with alignment . 63 includingspin–orbit coupling (DFT/PBE+SOC), which exhibit a blue shiftas the layer alignment changes from DJ toward RP, consistent withprior DFT studies in the literature.64 Second,we compute G0W0 quasiparticle band gaps (see section S2 of the Supporting Information for details) for a subset of the structuresanalyzed in Figure S1), indicating that this dependenceis predominantly dictated by the changes in the crystal structuregeometry. At large interlayer distances, DJ and RP perovskites yieldnearly identical band gaps, consistent with the expectation that theamount of vacuum between the layers is converging toward the monolayerlimit. A layer alignment of  (hereafter termed intermediate)yields a similar quasiparticle band gap trend.We start by investigating how the separation distancebetween adjacentinorganic layers  see 1a–c, imp4 (4AMP = 4-aminomethyl piperidinium),59 (C12DA)PbI4 ,65 PbI4 ,65 and (EOA)PbI4 (EOA = ethanolammonium),66 which sample DJ alignment with interlayer distances of10.5, 11.2, and 15.8 Å and intermediate alignment with an interlayer distance of 10.0 Å, respectively. Experimentaland model structures outline the same trend with quasiparticle bandgaps of experimental structures being slightly larger than those correspondingto models. We attribute the agreement with band gaps computed forthe models to a cancellation of errors originating from the absenceof both octahedral tilting and organic cations in the model structures.The former is expected to red-shift quasiparticle band gaps by >0.5eV67 , while the latter has been shown to blue-shift quasiparticleband gaps by >0.3 eV due to an underestimation of dielectric screening.52 Furthermore, we expect all our computed quasiparticle band gapsto be underestimated with respect to experiment by approximately 0.5eV, due to the DFT starting point sensitivity of G0W0 calculations,68 and on the basis of prior studies of excitedstates for halide perovskites69 (see section S2 of the Supporting Information). Taking into account these subtleties, the agreement betweenband gap trends computed for model and experimental structures supportsour starting assumption that calculations on model layered perovskitesshould capture the principal physical trends and, therefore, can beused to further explore excited state properties in a systematic way.In Figure S3 for representativeextended band structures). In addition to the red-shift in the quasiparticleband gap with shorter interlayer distances reported above, we alsoobserve an increase in the dispersion of the valence band edge alongthe high-symmetry A –M  direction, which corresponds in real space tothe direction perpendicular to the inorganic layer. The A–R direction, parallel to the inorganic layer in realspace, displays the opposite trend. At the same time, the conductionband edge along the A–M direction follows a similar yet moregradual change in band curvature than the valence band edge, whilethe A–R direction remains unaffected by the interlayer distanceor alignment. These observations are consistent with the calculatedcharge carrier effective masses shown in Table S3 and can be explained from the analysis of the orbital contributionat the conduction and valence band edges  computed for selectedexperimental structures confirm the trends extracted from model layeredperovskites, indicating that the interlayer distance and alignmentare the primary geometric parameters that can facilitate interlayerelectronic coupling, while small octahedral distortions and tiltingmay have a secondary effect.To rationalize the band gap trends shown in GW+BSE framework  for model layered perovskitesare shown in panels a and b of Figures S6 and S7 anddisplay an expected red-shift with a decrease in the interlayer distance shows very good agreement with measurements reportedin ref  and fordin ref . In alln ref , corresponding to the lowest(nondegenerate) bound state, where re and rh are position vectors for the electron and hole,respectively. First, we visualize the probability of localizationfor a photoexcited electron when the hole is fixed in an arbitraryposition, shown in Figure S8 for two differentinterlayer distances. We find that photoexcited electrons are stronglyconfined within a single inorganic layer for the larger interlayerdistance of 16 Å, in agreement with prior works18 . In contrast, The exciton binding energy is generally correlatedin isotropicmaterials with the average real space separation between photoexcitedelectrons and holes.Figure S8 may suggestthat exciton delocalizationcan be tuned by changing the interlayer distance in layered perovskites,it does not provide a quantitative assessment of this tuning vehicle.To compute this, we analyze the exciton correlation function (ECF),as introduced in ref ; the main advantage of evaluating this quantity isthat it is independent of the arbitrary choice of hole positions,in contrast with the qualitative pictures shown in panels a and bof Figure S8.While d in ref  and defi vector r,72  ECF∥ calculated for model DJ structures  displays a wider extentfor smaller interlayer distances. For all structures analyzed , the out-of-plane 1D ECF⊥ displays a narrow peak centered around 3.1 Å away from theorigin, indicating that bound electron–hole pairs in thesestates are most likely to be 3.1 Å apart .However, while the height of this peak is nearly 0.2 for model layeredperovskites with a large interlayer distance and/or RP alignment,it decreases sharply to ≤0.05 when the inorganic layers areDJ aligned and 10 Å apart . In the latter case, in addition to the main ECF peak, severalequally spaced peaks are clearly distinguished for larger electron–holedistances, consistent with an interlayer delocalization of the excitonwave function . We quantify the averageinterlayer electron–hole separation as described in section S4 of the Supporting Information andshown in D increasesfrom 10 to 12 Å for DJ aligned perovskites, with a slower decreasefor the intermediate aligned perovskites. Beyond an interlayer distanceof 12 Å, the average interlayer electron–hole separationremains roughly constant. In contrast, lowest-energy excitons areconfined within a single metal halide layer in all RP aligned structures,regardless of their interlayer distance.We use the ECF to quantify howextended the lowest-energy boundexciton is in layered perovskites and specifically analyze it in planeas shownin S11 displshownin S11 displshownin S11 displshownin S11 displOverall, our resultsdemonstrate that exciton delocalization acrossthe inorganic metal halide layers in is primarily driven by the electroniccoupling between neighboring apical halogen p orbitals. In sufficientlyclose proximity, the apical I-p orbitals dominating the VBT overlapwith one another and with the CBB wave functions and yield non-negligiblecontributions to the lowest-energy exciton wave function from pairsof single-particle states localized in separate inorganic layers.Excitons delocalized across layers correspond to states with a lowexcitation energy and a low exciton binding energy. Furthermore, dueto the interlayer electronic coupling, perovskites with small interlayerdistances exhibit absorption coefficients with similar magnitudesfor both in- and out-of-plane polarized light.GW+BSE calculationsfor a series of model and experimental structuresof layered organic–inorganic lead iodide perovskites to understandhow the distance and alignment of inorganic layers impact the excitedstate properties of this family of materials. We found that electronicand optical coupling of adjacent inorganic layers can be achievedby tuning the interlayer distance and relative layer alignment andis facilitated through the interaction of apical I orbitals from neighboringinorganic layers. We have shown for the first time that through interlayercoupling, it is possible to overcome the confinement of excitons ina single lead iodide layer and facilitate the interlayer delocalizationof bound electron–hole pairs in bulk layered perovskites. Theinterlayer distance in layered materials and heterostructures couldbe controlled in principle through applied pressure.74 However, strain-induced structural changes in both the inorganicand the organic layers may be more difficult to control in heterogeneousand soft layered perovskites and may have secondary effects on theelectronic structure.74 Unlike conventionallayered materials, tuning interlayer separation and alignment in layeredperovskites can also be realized intrinsically, through a judiciouschoice of the organic spacers.75 Here,we have shown that all physical trends extracted for model systemsare confirmed by explicit calculations for experimentally realizedlayered perovskites chosen as representatives of each structural feature.We hope that our work will provide a reliable starting point for futurestudies that aim to understand the role of phonons in the localizationof excitons, in these complex systems, using for example similar first-principlesapproaches to those recently reported in ref (76 and self-assembled bulk heterostructures,77 providing a potential pathway toward the exploration of layeredorganic–inorganic halide perovskites as functional materialsfor possible applications in excitonic devices.In summary, wehave performed state-of-the-art d in ref . Additio


We have previously reported that maternal obesity reduces placental transport capacity for lysophosphatidylcholine-docosahexaenoic acid (LPC-DHA), a preferred form for transfer of DHA (omega 3) to the fetal brain, but only in male fetuses. Phosphatidylethanolamine (PE) and phosphatidylcholine (PC), have either sn-1 ester, ether or vinyl ether  linkages to primarily unsaturated and monounsaturated fatty acids and DHA or arachidonic acid  in the sn-2 position. Whether ether and plasmalogen PC and PE metabolism in placenta impacts transfer to the fetus is unexplored. We hypothesized that ether and plasmalogen PC and PE containing DHA and ARA are reduced in maternal–fetal unit in pregnancies complicated by obesity and these differences are dependent on fetal sex.In maternal, umbilical cord plasma and placentas from obese women  and normal weight women , all PC and PE species containing DHA and ARA were analyzed by LC–MS/MS. Placental protein expression of enzymes involved in phospholipid synthesis, were determined by immunoblotting. All variables were compared between control vs obese groups and separated by fetal sex, in each sample using the Benjamini–Hochberg false discovery rate adjustment to account for multiple testing.Levels of ester PC containing DHA and ARA were profoundly reduced by 60–92% in male placentas of obese mothers, while levels of ether and plasmalogen PE containing DHA and ARA were decreased by 51–84% in female placentas. PLA2G4C abundance was lower in male placentas and LPCAT4 abundance was lower solely in females in obesity. In umbilical cord, levels of ester, ether and plasmalogen PC and PE with DHA were reduced by 43–61% in male, but not female, fetuses of obese mothers.We found a fetal sex effect in placental PE and PC ester, ether and plasmalogen PE and PC containing DHA in response to maternal obesity which appears to reflect an ability of female placentas to adapt to maintain optimal fetal DHA transfer in maternal obesity.The online version contains supplementary material available at 10.1186/s13293-023-00548-1. Ether and plasmalogen phosphatidylcholine (PC) and phosphatidylethanolamine (PE) are considered DHA reservoirs and whether their metabolism in placenta and DHA transfer to the fetus are altered in obesity is unexplored, especially regarding the fetal sex.We found that in obesity, (1) pregnancies with male fetuses decrease ester PC with DHA and ARA in placentas but not plasmalogen PC species and the levels of ester, ether and plasmalogen PC and PE with DHA is decreased in fetal umbilical circulation, and (2) pregnancies with female fetuses decrease ether and plasmalogen PE with DHA and ARA in placentas and maintain the levels of ester, ether and plasmalogen PC and PE with DHA in fetal circulation.Both males and females have compensatory mechanisms that attempt to maintain an adequate supply of DHA species, particularly for brain development, in obesity, however, the male placental adaptation failed to maintain fetal levels to those found in normal weight pregnancies.The online version contains supplementary material available at 10.1186/s13293-023-00548-1. Docosahexaenoic acid (DHA) is a critical omega 3 long chain polyunsaturated fatty acid (LCPUFA) for fetal brain development. We have recently reported that maternal obesity reduces placental transport capacity for LysophosPhatidylCholine-DHA (LPC-DHA), a preferred form for transfer of DHA to the fetal brain, but only in male fetuses. Other important lipids, the plasmalogen phosphatidylcholine (PC) and phosphatidylethanolamine (PE) are considered DHA reservoirs, but its roles in the maternal–fetal unit are largely unexplored. We examined these lipid species in maternal and fetal circulation and in placental tissue to uncover potential novel roles for ether and plasmalogen lipids in the regulation of placenta delivery of these vital nutrients in pregnancies complicated by obesity depending of fetal sex. We demonstrated for the first time, that female fetuses of obese mothers decrease placental ether and plasmalogen PE containing DHA and arachidonic acid , and show a high fetal–placental adaptability and placental reserve capacity that can maintain the PC-LCPUFA synthesis and the transfer of these crucial species to the fetus to preserve brain development. Our study also demonstrated that male fetuses, in response to maternal obesity, reduce the placental ester PC species containing DHA and ARA and reduce the ether and plasmalogen PE reservoir of DHA and ARA in fetal circulation. Our findings support a fetal sex effect in placental ester, ether and plasmalogen PE and PC containing DHA in response to maternal obesity which appears to reflect an ability of female placentas to adapt to maintain optimal fetal DHA transfer in maternal obesity.The online version contains supplementary material available at 10.1186/s13293-023-00548-1. The worldwide prevalence of maternal obesity continues to increase and affects not only maternal health, but also negatively impacts fetal growth and development by modulating placental function . Placent. Maternal n-3 LCPUFA deficiency has been reported in pre-gestational obese women 18:1 and LPC [2H7]18:1) and PE class (PE 15:0_[2H7]18:1 and LPE [2H7]18:1).Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) were extracted and analyzed in placental homogenates and plasma samples , by LC–MS/MS in the Mass Spectrometry Lipidomics Core facility at the University of Colorado using a protocol previously described , 36. BriIn order to distinguish vinyl ether  from 1-O-alkyl (O = ether) linkages at the sn-1 position of PC and PE species, acid labile plasmalogens were hydrolyzed by exposure to 12N HCl fumes . This wap values < 0.05 were considered as statistically significant.All statistical analyses were performed using GraphPad Prism version 9.01. Results are expressed as mean ± SD for each sample type; maternal vein (MV), placenta, umbilical vein (UV) and artery (UA). Chi-square test was used to compare qualitative data in obese and control groups. Data distribution was assessed by the Shapiro–Wilk normality test. All lipid variables were compared between two independent groups, control vs obese groups and separated by fetal sex, in each sample. We applied the Benjamini–Hochberg false discovery rate adjustment to account for multiple testing. All tests were two-sided. A significance threshold set at q ≤ 0.05 was used for the targeted lipidomic analysis . CorrelaIn addition, for each phospholipid variable showing a statistical difference between groups, effect size was calculated as following: ((Mean PC ob − Mean PC ctr)/ mean PC ctr) × 100).Clinical parameters of mothers and their infants are provided in Additional file We analyzed all the species of sn-1 ester (common form), ether and plasmalogen PC and PE containing DHA and ARA in maternal venous plasma, in placenta and in umbilical cord venous and arterial plasma by LC–MS/MS.Metabolic profile of obese mothers was characterized by lower ester, ether and plasmalogen PC and PE species containing DHA compared to normal weight mothers. Differences achieving statistical significance are presented in Fig. p = 0.025, reduced by 50%)  were evaluated in placenta homogenates  which hydrolyzes acyl groups from PC to form the lysophospholipid (LPC) form and found that PLA2G4C abundance was lower in male placentas of obese compared to control mothers  in three compartments: maternal circulation, placenta and fetal umbilical circulation. These changes may have consequences for placental function, birth weight, and fetal brain development as well as lipid signaling regarding the fetal sex. We found significant differences in levels of sn-1 ester, and particularly sn-1 ether and plasmalogen PC and PE containing DHA and ARA in all three compartments in pregnancies complicated by obesity and changes in placenta and cord plasma were highly sex specific. This is the first report to suggest that sn-1 ether and plasmalogen phospholipids containing crucial LCPUFA may play a key role in maternal to fetal transfer by the placenta, and possibly act as a reservoir of vital DHA and ARA for the fetus. We also speculate that the female placenta is able to compensate in the obese environment to more effectively deliver vital lipids to the fetal compartment.In the maternal circulation of obese women, we found lower levels in several phospholipid species with DHA, including sn-1 ester linked PE 16:0_22:6 and PE 18:0_22:6, sn-1 ether linked PE O-18:0_22:6 and sn-1 plasmalogen linked PC P-16:0_22:6 and PE P-18:0_22:6 but we found no differences in ARA linked phospholipids , cellular storage form, are synthesized at the expense of incorporation of DHA and ARA into phospholipids. In our previous study, we have shown that DHA and ARA levels in total TG remained stable in both male and female placentas of obese women while the non-esterified form of both FAs were decreased along with a trend to be decreased in total phospholipid pool only in male placenta. This indicates a possible preferential mobilization of DHA and ARA toward the triglyceride form . Since oInterestingly, we show a specific decrease of particular sn-1 ether and plasmalogen PE species with DHA and ARA in placentas from obese mothers carrying female fetuses , that acylates dihydroxyacetone phosphate (DHAP) with a fatty acyl-CoA at the sn-1 position and the alkylglycerone phosphate synthase (AGPS) that catalyzes the exchange of the fatty acyl group of 1-acyl-DHAP for a fatty alcohol . HoweverDespite the unchanged expression in FAR1 enzyme, lower DHA supplied in the plasma of obese mothers may alter the ether and plasmalogen PE and PC synthesis outside the peroxisome. Indeed, phospholipid synthesis is completed at the ER mediated by specific enzymes involved in the de novo Kennedy pathway and remodeling pathways (Land’s cycle) . We foun2G4C (iPLA2) protein expression in male but not in female placentas  metabolites including SM containing very long chain fatty acid, such as nervonic acid (24:1). This fatty acid is exclusively catabolized in the peroxisome and its breakdown is considered a source for alkyl groups in plasmalogen synthesis . InverseLower levels of ether and plasmalogen phospholipids at birth in male infants Table  may be a2 and calcium-independent iPLA2 in the frontal cortex in rodents and subsequently downregulates the brain phospholipid remodeling pathway [Although the effect of decreased DHA supply on brain growth and development remains to be fully established, we speculate that altered placental PC-DHA metabolism and less DHA availability in circulation of male fetuses exposed to obesity may negatively influence the development of the brain, programming early life neurodevelopmental disorders. Indeed, dietary n-3 fatty acid deficiency reduces DHA-regulated PLA pathway .The mechanisms that drive the sex-specific adaptations that we show in the placental phospholipid metabolism including the ether linked PC and PE containing DHA and ARA in the setting of obesity Fig.  remain lLimitations of this study include the small number of enrolled women and smaller sample size in each fetal sex group and lack of dietary information from the pregnant women. In addition, we were not able to find acceptable antibodies for many peroxisome and lipid synthesis enzymes involved in ether and plasmalogen synthesis. One of the major strengths of the study is that we have specifically identified the plasmalogen and ether linked phospholipids and analyzed those species in maternal and umbilical cord plasma as well as placentas of healthy mothers and those complicated by obesity and that those maternal–placental–fetal samples provide from the same pregnancy.We show that maternal obesity reduces the content of placental PC and PE containing LCPUFA differentially in women carrying male compared to female infants. This difference has potential consequences on supply of this preferred lipid form for fetal brain development with short- and long-term consequences. This study is the first to explore the two important phospholipids; PC and PE containing DHA and ARA, and examined sn-1 ester, ether and plasmalogen linkages, in maternal and fetal circulation and in placental tissue to uncover potential novel roles for ether and plasmalogen lipids in the regulation of placenta delivery of these vital nutrients in pregnancies complicated by obesity. By decreasing all ether and plasmalogen PE, species which are considered a reservoir for DHA and ARA in the placenta, female fetuses of obese mothers show a high fetal–placental adaptability and placental reserve capacity that can maintain the PC-LCPUFA (including LPC-DHA) synthesis and the transfer of these crucial species to the fetus to preserve growth and brain development. Male fetuses, in response to maternal obesity, reduce the placental ester PC species containing DHA and ARA as well as reduce the ether and plasmalogen PE reservoir of DHA and ARA in fetal circulation. Both males and females appear to have compensatory mechanisms that attempt to maintain an adequate supply of LCPUFA species for fetal organ growth, in particular the brain. The adaptation in females maintains normal levels of DHA and ARA in the umbilical circulation while lower plasmalogen PE LCPUFA contents in the male umbilical circulation at birth appears to be a failure of the adaptive responses. This could explain, in part, the male fetus being more vulnerable to the long-term detrimental consequences of gestation in the environment of maternal obesity. Further molecular studies will help to better understand the mechanism of ether and plasmalogen phospholipids in maternal–fetal unit and the role of fetal sex.Additional file 1. Supplemental data.


Dear Editor1, the use of preoperative α-adrenoceptor blockade (AAB) to prevent cardiovascular complications during phaeochromocytoma surgery continues to be debated2. Proponents of pretreatment see the widespread adoption of AAB in the 1960s3 as instrumental in improving surgical results. Opponents of pretreatment, on the other hand, argue that improved diagnostics with increased detection of phaeochromocytoma as adrenal incidentalomas, the advent of minimally invasive surgery, and improved anaesthetic practices have contributed to making contemporary phaeochromocytoma surgery safe. Indeed, a review4 of contemporary management from 21 centres worldwide published in this journal showed varying perioperative practices, and similar results with and without AAB, with an overall cardiovascular complication rate of 5 per cent and mortality rate of 0.5 per cent. However, the evidence base is weak and prospective data are lacking.Although recommended by current guidelinesIn this pilot study conducted at Sahlgrenska University Hospital, Gothenburg, Sweden, the feasibility of phaeochromocytoma surgery without AAB was investigated using a structured prospective protocol. All consecutive patients with newly diagnosed phaeochromocytoma between May 2017 and December 2019 were assessed for eligibility. Inclusion criteria were: newly diagnosed unilateral catecholamine-producing adrenal tumour, age over 18 years, and intended minimally invasive surgery. Exclusion criteria were: haemodynamic instability requiring intensive care, malignant hypertension (severe hypertension with secondary organ damage), symptomatic impaired cardiac function (New York Heart Association class III–IV), and pregnancy. The primary outcome variable was perioperative haemodynamics, defined as number of episodes of systolic BP over 200 or below 70 mmHg, monitored via arterial catheters and registered at least every 5 min. Secondary outcome variables were episodes of SBP over 180 or below 100 mmHg, time needed for surveillance in the postoperative ICU, use of inotropic agents when postoperative mean arterial pressure (MAP) reached levels below 65 mmHg, and total duration of inpatient stay. The study was approved by the regional ethical review board in Gothenburg (754-15). Informed consent was signed by all patients in the study group, but was not required for the control group as these patients were included retrospectively.Table S1).Of 15 patients available for assessment, 5 were excluded . Ten patients diagnosed with phaeochromocytoma between 2017 and 2019  were therefore included and underwent minimally invasive adrenalectomy without AAB as soon as possible after inclusion. Surgery was performed under general sevoflurane-based anaesthesia aiming to maintain MAP over 65 mm Hg, systolic BP below 180 mm Hg, and heart rate under 100 b.p.m. These patients were compared with 10 age-matched controls from the authors’ institutional phaeochromocytoma database (240 patients) who had received traditional preoperative AAB treatment between 2003 and 2018 . Nine patients in the study group and only 2 in the control group received vasodilator infusions during surgery (Table S1). There was no significant difference between the study group and the control group with regard to tumour size or hormone profile . Patients without preoperative AAB spent significantly less time in postoperative surveillance immediately after surgery , as well as in hospital overall.There was no significant difference in perioperative or postoperative haemodynamics between the groups (1. An RCT using haemodynamic instability5 as endpoint is reasonable and may be feasible.In conclusion, omitting AAB before surgery in patients with phaeochromocytoma does not seem to increase perioperative or postoperative haemodynamic instability, and can shorten both the time in postoperative surveillance units and the overall duration of hospital stay. These data do not, therefore, support current guidelines on phaeochromocytoma management, which recommend treatment with AAB for 7–14 days before surgery to decrease the risk of perioperative haemodynamic instabilityznac201_Supplementary_DataClick here for additional data file.