The Genetic Landscape of Pediatric Postural Orthostatic Tachycardia Syndrome

Background: Postural orthostatic tachycardia syndrome (POTS) is a complex disorder with serious health consequences, while its etiology remains largely elusive.

To investigate the genetic landscape of POTS using genomic approaches in a unique pediatric cohort.

We conducted a combined genome wide genotyping and whole exome sequencing (WES) study to systemically examine the molecular mechanisms of POTS pathogenesis. The patients for were genotyped as two independent cohorts, a family cohort of 100 complete families and a case control cohort of 207 unrelated European cases and 4,063 ethnicity-matched controls. The WES component consisted of a subset of the genotyped subjects, including 87 unrelated European cases and 2,719 unrelated European controls.

Due to the heterogeneous phenotype of POTS, unlike traditional phenotypes for association study, it is unlikely that any loci will reach genome-wide significance. Instead, we conducted an over-representation analysis (ORA) by considering all genes that showed nominal significance. The ORA identified gene sets linked to Cell-Cell Junction, Early Estrogen Response, and Substance-Related Disorders, with statistical significance. Moreover, WES revealed 55 genes with genome-wide significance through rare variant burden analysis, harboring 92 variants classified as pathogenic or likely pathogenic by ClinVar.

and Relevance: This study showcases the complex interplay between common and rare genetic variants in POTS development, marking an pioneering step forward in deciphering its complex etiologies. The insights gained from this research enriches our understanding of POTS, offering new avenues for precise treatment strategies and highlighting the need for continued research in this area.

burden analysis; estrogen response; gene-based association; pathogenic variant; dysautonomia All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint

Postural orthostatic tachycardia syndrome (POTS) is a dysautonomia condition characterized by persistent excessive upright tachycardia upon assuming an upright position, without concurrent orthostatic hypotension1-4. Chronic orthostatic intolerance caused by POTS leads to severe functional impairment and psychological distress to the patients, seriously affecting patients’ lives. Patients with POTS often experience a wide array of symptoms, including severe lightheadedness, palpitations, cognitive impairment, debilitating fatigue, disruptions in sleep patterns, varying levels of pain, recurrent headaches, and gastrointestinal disturbances. POTS was only formally recognized as a distinct medical condition in 1993 5. POTS affects about 0.2% to 1.0% of the US population, and is more frequently seen in women1,2,6. The connection with sex remains poorly understood. Both children and adults can be affected, while a majority of patients were diagnosed prior to reaching menopause 7,8. The tachycardia in POTS can be due to any of the many factors affecting venous return and cardiac stroke volume, e.g. inability to maintain peripheral vascular tone, low blood volume, or increased pooling in the splanchnic circulation and extremities9. While anxiety is common, it is not considered as a significant causal factor. Despite extensive research, the complex pathophysiology of POTS remains only partially understood. In light of the elusive nature of POTS' etiology, our study employed an integrative OMICS approach to explore the molecular underpinnings of its pathogenesis in a unique pediatric cohort. Previous research has suggested a genetic link to POTS, such as the identification of the A457P mutation in the SLC6A2 gene (encoding norepinephrine transporter) causing POTS10. In our study, genome-wide genotyping of common variants and exome sequencing for rare variants were applied. Unlike traditional genome-wide association study (GWAS) phenotypes, it is unlikely that any loci will reach genome-wide significance due to the heterogeneous phenotype of POTS. Increasing the sample size may not be effective as it also complicates the heterogeneity. Instead, focusing on common variants, we aimed to identify gene sets tagged by common single nucleotide polymorphisms (SNP) that are over-represented in POTS patients. Through the exome sequencing, we aimed at identifying rare coding genetic variants in the candidate genes uncovered that may contribute to the disorder's heterogeneous etiology. By centering on pediatric POTS patients, our study offers a unique perspective on the genetic landscape of this condition, potentially revealing insights into its complex mechanisms.

1. GWAS 1.1 Subjects Participants were enrolled through the POTS Program at the Children's Hospital of Philadelphia (CHOP). POTS patients aged 18 years or younger at the time of diagnosis were eligible for this study. We invited patients and their families to join this study through letters or emails. Those with DNA samples available from both parents were included in the family cohort. Unrelated patients lacking parental DNA samples were included in the case-control cohort. We obtained informed consent from all subjects or, if subjects are under 18, from a parent and/or All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint legal guardian with assent from the child if 7 years or older. The CHOP Institutional Review Board (IRB) approved this study. 1.2 Genotyping The genotyping was done using the Illumina Infinium Global Screening Array (Illumina, San Diego, CA) with >700,000 SNPs genotyped. Altogether, 93.5% SNPs had a calling rate>99%, and the average calling rate of each DNA sample was 98.2%. Genome-wide imputation was done with the TOPMed Imputation Server (https://imputation.biodatacatalyst.nhlbi.nih.gov/# !) using the TOPMed (Version R2 on GRC38) Reference Panel. Altogether, 19,537,894 autosomal single nucleotide variants (SNV) with quality R2 ≥ 0.3 were included in this study. 1.3. Genotyping data analysis: In this study, the family cohort was tested by transmission disequilibrium test (TDT), which is immune to spurious associations from population stratification11. Kinship between family members in the family cohort was validated by identity by descent (IBD) analysis based on the auto-chromosomal genotyping data. Loci with Mendelian errors > 3 were removed from association test. In addition, previous study has emphasized that replicated sequences in autosomes and sex chromosomes cause sex-related bias on the genotyping of autosomal SNPs 12. As an additional quality filter, we tested sex effect by comparing mothers and fathers in the family cohorts. All SNPs with sex effect P<0.05 were removed. For the case-control cohort, unrelated cases were identified of European ancestry (EA) by principal component analysis (PCA) with genome-wide SNP markers, and were confirmed of non-relationship by identical-by- descent (IBD) analysis. European controls were selected by matching ethnicity based on the PCA analysis. Correction for population stratification was done by logistic regression using the first ten principal components as covariates 13. The IBD analysis, TDT test, and case-control association test, were done using the PLINK software v1.9 (http://pngu.mgh.harvard.edu/purcell/plink/)14. All SNPs with Hardy-Weinberg Equilibrium (HWE) P<0.01 in European controls were removed from further analysis. Gene-based association test was done by the Versatile Gene-based Association Study - 2 version 2 (VEGAS2v02) software 15,16. 2. WES 2.1 Subjects Based on the genotyping data, we identified 87 unrelated European cases (61 females and 26 males) with non-relationship validated by the IBD analysis, and European ancestry validated by the PCA analysis. The cases were compared with the Non-Finish European (NFE) population in the Exome Aggregation Consortium (ExAC) database 17, using the Test Rare vAriants with Public Data (TRAPD) software18. Considering the potential inflation with the public database controls, the cases were further compared with 2,719 unrelated European non-POTS controls that have been sequenced by WES at the Center for Applied Genomics (CAG) of the Children’s Hospital of Philadelphia (CHOP). 2.2 Library Preparation and Sequencing All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint Paired-end sequencing was performed on the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA), using an S4 flowcell with run parameters of 101 x 10 x 10 x101 [Read 1 x Index 1 (i7) x Index 2 (i5) x Read 2]. Demultiplexing, alignment, and variant calling processes were performed on the Illumina DRAGEN Bio-IT Platform (version 3.3.7) using the 1000 Genomes Project Reference Human Genome Sequence (hs37d5). Alignment metrics were calculated using the Picard (version 2.18.27) CollectHsMetrics tool. 2.3 Burden analysis of variants of interest (VOI) and pathogenic (P) or likely pathogenic (LP) Variants The genetic variants which have minor allele frequency (MAF) greater than 0.001 in the NFE population based on the ExAC database17 have been excluded. Functional candidate VOIs were selected by the prediction results with at least 1 of a number of genetic variant prediction softwares, i.e. SIFT_pred="D" or Polyphen2_HDIV_pred="D" or Polyphen2_HDIV_pred="P" or Polyphen2_HVAR_pred="D" or Polyphen2_HVAR_pred="P" or LRT_pred="D" or MutationTaster_pred="A" or MutationTaster_pred="D" or MutationAssessor_pred="H" or MutationAssessor_pred="M" or FATHMM_pred="D" or PROVEAN_pred="D" or MetaSVM_pred="D" or MetaLR_pred="D", based on the annotation with the ANNOVAR software 19. The mutation burden in cases and controls were counted with the TRAPD software18. We have optimized the TRAPD algorithm with normalized genome coverage to capture causal variants with effects in the same directions.20 Gene-wide burden test of the candidate variants in the cases was done by one tailed Fisher exact test, compared with the ExAC NFE controls by dominant inheritance model. Multiple comparisons were corrected by Bonferroni correction. Assuming 21,306 protein-coding genes in human genome 21, the genome- wide significance of the burden test was defined as α =0.05/21,306=2.347E-06. In further, deleterious variants were identified from the functional candidate variants according to the aggregated information by ClinVar annotation 22,23, InterVar prediction24, and the Human Gene Mutation Database (HGMD) classification25.

1. Subjects All POTS patients in this study were Caucasian with the age of diagnosis ranging from 12 years old to 21 years old, and median diagnosis age (Q1, Q3) of 15.6 (13.2, 17.8) years7. The patients were evaluated as two independent cohorts, a family cohort and a case control cohort. The family cohort included 114 POTS cases (including 28 males and 86 females) from 100 complete families. We included 62 unaffected siblings from these families in this study. Significant comorbidities were detected in 18 unrelated patients from the family cohort (Table 1). The case control cohort included 207 unrelated cases (including 53 males and 154 females). Among the 207 cases, comorbidities were seen in 24 unrelated patients (Table 1). From the 207 cases, 194 unrelated cases (including 44 males and 150 females) based on genome-wide genotyping were compared with 4,063 European controls for genetic association test. 2. GWAS results All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint The inherently heterogeneous phenotype of POTS presented significant challenges. Achieving genome-wide significance for any particular genetic loci was improbable by increasing sample size. Instead, we conducted an over-representation analysis (ORA) by considering all genes that showed nominal significance. Our conclusions were only drawn based on ORA analysis with solid statistical evidence. In this study, 5,670 SNPs were identified of potential association signals with P<0.05 in both the family cohort and the case-control cohort, with effects in the same direction. The summary statistics are available in Supplementary Table 1. As shown, none of these loci showed genome-wide significance. Consequently, we performed gene-based association test at these loci. As shown in Supplementary Table 2, 716 genes showed association P<0.05 in both the family cohort and the case-control cohort, a number significantly higher (P=1.81E-128) than the 53 genes expected by chance (i.e., 21,306 × 5% × 5%), assuming there are 21,306 human coding genes. Using the WebGestalt (WEB-based Gene SeT AnaLysis Toolkit) web tool 26, over- representation analysis (ORA) of the 716 genes by the DisGeNET approach27, the Gene Ontology (GO) Cellular Component28, the GO molecular function28, the MSigDB Hallmark gene sets29, and the Human Phenotype Ontology (HPO)30, underscored several gene sets of statistical significance (FDR<0.1), with common genetic variants contributing to the susceptibility of POTS (Table 2). 3. Burden analysis of VOIs By WES, 10,199 functional rare coding variants from 6,566 autosomal genes were called and annotated using the ANNOVAR software19. The gene burden analysis of these variants is shown in Supplementary Table 3. Considering the potential inflation with public database controls by TRAPD18, the cases were further compared with 2,719 unrelated European non-POTS controls that have been sequenced by WES at CAG. Significant genes were defined as genome-wide significant by comparing to both public database controls and the internal controls. As the results, 55 genes showed genome-wide significance (P<2.347E-06, Table 3). Among the 55 genes, 7 genes (ABCA13, CELSR1, DAB2IP, DNAH1, DNAH2, DNAH3, SYNE2) had nominal significance in the gene-based GWAS study [gene enrichment: 7/716 (gene-based GWAS) vs 55/21,306 (human coding genes), OR=3.81, P=3.52E-04], which suggests the association signals of these genes in GWAS may be explain by rare coding variants. ORA analysis of the 55 genes highlighted the roles of the genes in muscular function, emphasizing muscular dysfunction in the pathogenesis of POTS (Table 4). 4. Pathogenic/Likely Pathogenic (P/LP) variants Our study identified 107 deleterious P/LP variants, of which 99 deleterious variants were supported by a minimum of two databases, including ClinVar (clinvar_20231230), InterVar, or HGMD_Pro_2023.3. When we concentrated on variants classified as P/LP variants by ClinVar classification, 92 P/LP variants were highlighted, including 3 variants that were previously reported of dominant genetic effects (Supplementary Table 4). Among the 87 WES patients, 53 (60.9%) have at least one P/LP variant (Supplementary Figure 1). The 92 P/LP variants are from 87 genes. Five genes, i.e., GAA, GALT, GYS2, PAH, and USH2A, each have two P/LP variants from two different individuals. The gene with P/LP variant, OTOG, has also been identified of nominal significance in the gene-based GWAS study. ORA analysis of the 87 genes highlighted All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint a number of gene sets with statistical significance (FDR<0.1), suggesting the possibility of several underexplored gene pathways and networks in the pathogenesis of POTS (Table 5).

1. Common genetic variants and POTS susceptibility This study presents a unique approach to a systemic evaluation of the etiology and molecular mechanisms of POTS. The application of GWAS to POTS has encountered challenges, primarily due to the disorder's extensive phenotypic heterogeneity. This heterogeneity poses a significant obstacle for GWAS, which typically depends on a well-defined, uniform phenotype to effectively identify common genetic variants linked to a specific condition. A major challenge in GWAS for POTS is accurately characterizing its diverse phenotypes. The clinical complexity of POTS makes it difficult to distinguish between potential subtypes and to define a consistent phenotype that truly represents the disorder. Given the substantial phenotypic diversity of POTS, the GWAS approach was unable to identify any loci of genome-wide significance. Nevertheless, genes that showed nominal significance in gene-based association tests exhibited a highly significant enrichment in several gene sets important to POTS physiobiology. This finding underscores the role of common genetic variants in influencing POTS susceptibility and provides insights into its pathophysiology (Table 2). 1.1 GO Cellular Component Cell-cell junction (GO:0005911) and synaptic membrane (GO:0097060): These gene sets are integral to neuronal communication, which is crucial for the proper functioning of the ANS. Genes associated with cell-cell junctions play a role in maintaining the structural and functional integrity of synapses 31, the points of communication between neurons. Synaptic membrane genes are involved in neurotransmitter release and reuptake32, which are critical for signal transmission in the ANS. Common genetic variations in genes associated with these processes can influence autonomic responses, a hallmark of POTS. Neuronal cell body (GO:0043025) and axon part (GO:0033267): Genes associated with the neuronal cell body and axon are crucial for the health and function of neurons. Axonal genes play a role in the transmission of electrical signals along the nerve fiber33. Changed function in these cellular components by genetic variants can lead to impaired transmission of autonomic signals, contributing to the risk of orthostatic intolerance and tachycardia in POTS. Additionally, there is increasing evidence to suggest that a significant number of POTS patients experience small fiber neuropathy (SFN), an autoimmune disorder that specifically targets and damages the small fibers responsible for conducting autonomic and pain signals 34,35. This further underscores the importance of understanding the genetic and cellular mechanisms underlying neuronal function and integrity. Transporter complex (GO:1990351): This gene set is involved in the transport of various molecules across cellular membranes, including neurotransmitters 36. In the context of POTS, the regulation of neurotransmitters like norepinephrine is particularly relevant. Dysregulation in neurotransmitter transport can lead to imbalances in sympathetic nervous system activity, a critical aspect of POTS pathophysiology37. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint 1.2 GO Molecular Function Cell adhesion molecule binding (GO:0050839): Genes involved in cell adhesion molecule binding play a crucial role in the interaction and adhesion of cells to their surrounding extracellular matrix and to other cells38. This is particularly important in the cardiovascular system, where endothelial cell integrity is essential for maintaining vascular function. In POTS, the dysregulation of this function could lead to compromised blood vessel reactivity and integrity, influencing blood flow dynamics. Actin binding (GO:0003779): Actin is a fundamental component of the cellular cytoskeleton and is critical in various cellular processes, including maintenance of cell shape, cell movement, and muscle contraction39. Actin-binding genes are essential for the proper functioning of muscle cells, including cardiac40 and smooth muscle cells that line blood vessels41. In POTS, abnormalities in actin binding could impact cardiac muscle function and vascular tone regulation, both of which are vital for maintaining stable blood pressure and heart rate. Motor activity (GO:0003774): This gene set is associated with the generation of force and movement within cells, a function that is crucial in muscle cells, including the heart 42. In the context of POTS, motor activity genes could influence how heart and vascular muscles respond to autonomic signals, especially in adjusting heart rate and vascular tone in response to orthostatic stress. 1.3 Early Estrogen Response (HALLMARK_ESTROGEN_RESPONSE_EARLY): POTS is observed to be more common in women, with a ratio of as much as 5 females to 1 male43. However, the link with sex is not well comprehended. There is a recognized association between female hormones, notably estrogen, and changes in blood volume and vascular function44. This gene set comprises genes that are responsive to estrogen in the early phase of its action45. These early estrogen response genes could potentially play a role in POTS, given the higher prevalence of the condition in women. The potential effects include: (1) Autonomic regulation and cardiovascular effects: Estrogen is known to influence autonomic regulation and cardiovascular function 46, which are both key aspects in the pathophysiology of POTS. (2) Extended Thoracic Hypovolemia: Estrogen can affect fluid retention and blood vessel constriction47,48, potentially influencing the degree of hypovolemia and the strain on the autonomic nervous system. (3) Autoimmune Responses: Estrogen can modulate immune responses 49, which might intersect with autoimmune processes targeting the autonomic nervous system in POTS. Furthermore, females have a higher prevalence of autoimmune disorders compared to males 50. (4) Inflammatory Mechanisms: Estrogen has both pro-inflammatory and anti-inflammatory effects, depending on the context51. The early estrogen response genes might play a role in the inflammatory underpinnings of POTS. (5) Autonomic Neuropathies and Sympathetic Denervation: Estrogen influences nerve function and repair52. Its early response genes could be involved in the development or compensation of autonomic neuropathies in POTS. (6) Impaired Norepinephrine Reuptake: Estrogen can modulate the expression and function of neurotransmitter transporters, possibly impacting norepinephrine reuptake mechanisms 53. Clinically, we observed a case series of three transgender females transitioning to males whose POTS symptoms significantly improved after the addition of exogenous testosterone 54. Additionally, both published50 and our unpublished data have observed that female POTS patients experience a worsening of symptoms around their menstrual periods. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint 1.4 Substance-Related Disorders (DisGeNET C0236969): This correlation carries two implications: firstly, POTS may share a common genetic susceptibility with substance-related disorders; secondly, this gene set might be linked to POTS due to the role of certain substances in modulating the autonomic nervous system and cardiovascular responses. Dysautonomia can be exacerbated or triggered by substance exposure. The underlying mechanisms may include: (1) The autonomic nervous system may be influenced by various medications commonly utilized in clinical practice 55. For example, β -adrenergic receptors are activated by some bronchodilators for asthma management. Amphetamines, like those prescribed for attention deficit hyperactivity disorder, or consuming caffeine, can lead to an increase in the release of the sympathetic neurotransmitter norepinephrine. Tricyclic antidepressants can inhibit the reuptake of norepinephrine, thus increasing its availability in the synaptic cleft 56. (2) Common substances can exert direct or indirect effects on the cardiovascular system, like caffeine, alcohol, nicotine, and antidepressants 57. Calcium channel blockers may cause peripheral vasodilation and reduce venous return58, thus exacerbate the hypovolemic state often seen in POTS. β -blockers may influence myocardial contractility or heart rate, contributing to the dysregulation of cardiovascular function. (3) Substances can also alter the body’s response to stress, a factor that is often implicated in the exacerbation of POTS symptoms 59. The dysregulation of stress hormones and the sympathetic nervous system can lead to increased heart rate and blood pressure variability. These gene sets offer a window into the complex interplay of common genetic variants and their potential role in predisposing individuals to POTS. The exploration of GWAS gene sets in the context of POTS not only enhances our understanding of the genetic basis of the syndrome but also opens new pathways for personalized and preventive healthcare strategies. 2. Rare functional variants and POTS heterogeneity Compared to the results of our GWAS study, our WES study emphasizes the importance of rare coding variants in the pathogenesis of POTS. Two complementary analyses were employed in this study: the burden analysis of rare variants and the identification of P/LP variants. The burden analysis entails assessing the cumulative impact of rare functional variants in the individuals with POTS compared to the control group. The primary focus is to determine whether there is a higher prevalence of functional rare variants in the POTS patients, as opposed to common variants identified in the association study. This analysis does not necessarily prioritize the predicted pathogenicity of each variant. Instead, it focuses on evaluating the overall burden of these functional rare variants in the genome, providing a comprehensive overview of the genetic landscape. Conversely, the analysis of P/LP rare variants involves identifying deleterious variants, particularly those classified by ClinVar. This can help establish a direct link between specific genetic changes and POTS, leading to a better understanding of the molecular mechanisms of the disease and potentially guiding targeted treatments. 2.1 Insights gained by burden analysis of VOIs Using 2,719 unrelated European controls, this study identified 55 genes associated with POTS with genome-wide significance by burden analysis of rare coding variants. The 55 genes identified in this study highlight both known and also unveil novel knowledge of POTS heterogeneity. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint 2.1.1 Muscular dysfunction in POTS The ORA analysis in this study emphasized the importance of possible muscular dysfunction in POTS, with genes involved in muscle function and muscular diseases enriched with highly statistical significance (Table 4a,e). Altogether, 32 out of the 55 genes are related to muscular dysfunction. The affected muscular function may not be limited to myocardium and vascular smooth muscle. For instance, the calf muscle pump generates pressure gradient between the thigh and the lower leg veins, and is the major force for return of venous blood from the lower extremities to the heart60. Decreased calf muscle pump activity (HP:0003690 Limb muscle weakness) may thus contribute to the venous pooling in lower extremities in some POTS patients61. It's worth noting that no muscle dysfunction has been observed in these POTS patients, suggesting that any potential involvement of muscular mechanisms may be subclinical in terms of skeletal muscle dysfunction. Muscular function relies on coordinated activity between muscle fibers and the metabolic and regulatory machineries62. The structural components of muscle cells that may be affected by rare coding variants include (Table 4b): (1) Contractile fiber (GO:0043292), sarcolemma (GO:0042383), and sarcoplasm (GO:0016528). The genes with rare coding variants include AHNAK nucleoprotein (AHNAK), calcium voltage-gated channel subunit alpha1 D (CACNA1D), cardiomyopathy associated 5 (CMYA5), myosin heavy chain 7B (MYH7B), nebulin (NEB), nebulin related anchoring protein (NRAP), obscurin, cytoskeletal calmodulin and titin-interacting RhoGEF (OBSCN), plectin (PLEC), ryanodine receptor 1 (RYR1), spectrin repeat containing nuclear envelope protein 2 (SYNE2), titin (TTN), and xin actin binding repeat containing 2 (XIRP2). (2) Extracellular matrix (GO:0031012). The genes with rare coding variants are agrin (AGRN), cartilage intermediate layer protein (CILP), collagen type XII alpha 1 chain (COL12A1), collagen type XXVII alpha 1 chain (COL27A1), collagen type VII alpha 1 chain (COL7A1), filaggrin (FLG), heparan sulfate proteoglycan 2 (HSPG2), laminin subunit alpha 5 (LAMA5), and usherin (USH2A). (3) Cell-substrate junction (GO:0030055). The related genes with rare coding variants are AHNAK, Rho GTPase activating protein 22 (ARHGAP22), FAT atypical cadherin 1 (FAT1), heparan sulfate proteoglycan 2 (HSPG2), NRAP, PLEC, SYNE2, and XIRP2. The molecular functions of these genes are related to the dynein motor to generate force, cytoskeletal actinin /ankyrin/actin binding, and ATPase activity for providing energy (Table 4c). 2.1.2 Microtubule dysfunction in POTS Among the 32 genes that are related to muscular dysfunction, four dynein axonemal heavy chain (DNAH) genes DNAH1, DNAH2, DNAH3, DNAH10, and the SYNE2 gene involve microtubule function. Axonemal dynein produces force to move other proteins and cell materials by microtubules within cilia 63. Dysfunction in endothelial cilia contributes to aberrant fluid- sensing and results in vascular disorders, including hypertension64. In addition, an intact microtubule network is necessary for proper subcellular structure and function65. Aberrant growth of cardiomyocyte microtubules contribute to contractile dysfunction66. Targeting at microtubules may improve cardiomyocyte function in human heart failure67. SYNE2 encodes nuclear envelope spectrin-repeat protein (Nesprin)-2, functioning as intracellular scaffolds and linkers to establish nuclear-cytoskeletal connections by binding cytoplasmic F-actin, in addition to its role as a microtubule scaffold 68. Mutations of SYNE2 may lead to structural and adaptive signaling defects in mechanically stressed tissues such as muscle, and cause Emery-Dreifuss All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint muscular dystrophy (EDMD5)69. Besides the above genes, two additional genes, kinetochore associated 1 (KNTC1) and RP1 like 1 (RP1L1) also encode proteins of the microtubule complex (GO:0005874). Notably, there has been no observed contractile dysfunction in these POTS patients, implying that any potential engagement of microtubule mechanisms may manifest subclinically concerning contractile function. 2.1.3 Genes reported of association with blood pressure According to the GWAS catalog, 15 of the 55 genes have been reported of association with blood pressure regulation (https://www.ebi.ac.uk , accessed on Sep 5, 2021), including 7 genes related to muscular function (ARHGAP22, CACNA1D, DNAH2, DNAH3, PLEC, SACS, TTN) with 8 other genes contributing (ARID1B, BAHCC1, CSMD1, LRP2, NUP160, PKD1, RP1L1, ZFHX3). The genes involved in muscular function may be related to POTS by their roles involving myocardium or vascular smooth muscle function. For example, the 2 DNAH genes DNAH270,71 and DNAH372 are associated with systolic blood pressure, while DNAH3 is also reported of association with diastolic blood pressure72. The association of DNAH2 and DNAH3 with blood pressure may be related to their roles in cardiomyocyte function66 (for systolic blood pressure), and microtubule function in vascular smooth muscle contraction73. However, clinically, no contractile dysfunction has been demonstrated in POTS so far, suggesting the need for further investigation into the underlying mechanisms. The LDL receptor related protein 2 gene (LRP2) encodes the endocytic receptor megalin, which has regulatory effects on the renin-angiotensin system activity in the kidney74, in addition to its key roles in renal proximal tubular function75. 2.1.4 Genes reported of association with heart rate Among the 55 genes, 10 genes have been reported of association with heart rate, including 4 genes related to muscular function (CACNA1D, COL12A1, PLEC, TTN) and 6 other contributing genes (CELSR1, CSMD1, DAB2IP, EPHB4, RP1L1, ZFHX3) (https://www.ebi.ac.uk , accessed on Sep 5, 2021). Among the 10 genes, the genes CACNA1D, CSMD1, PLEC, RP1L1, TTN, and ZFHX3, are also associated with blood pressure. DAB2IP associated with heart rate76 encodes a Ras GTPase-activating protein. In addition to its role as a tumor suppressor77, DAB2IP protein functions as a scaffold protein and modulates different signal cascades associated with cell proliferation, survival, and apoptosis.78 Through the DAB2IP-ASK1- JNK signaling pathway, DAB2IP plays important roles in the function and apoptosis of vascular endothelial cells79. CELSR1 encodes a member of the flamingo subfamily of the cadherin superfamily80, with important roles in neuronal morphogenesis81. Mutations of this gene has been reported of correlation with neural tube defects82. CELSR1 was reported of association with heart rate in heart failure patients by a previous GWAS83. Concerning the potential roles of CELSR1 in regulating heart rate and in POTS, vestibular hair cells of the inner ear convert mechanical stimuli into neural activity, thus to control balance, blood pressure and heart rate84. CELSR1 coordinates the planar polarity organization of vestibular hair cells in inner ear development85. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint Meanwhile, we have observed patients who still have vestibular dysfunction clinically, even without a history of head trauma or concussion. 2.1.5 Cardiac insufficiency resulting from genetic mutations In addition to the knowledge gained from the gene set enrichment analysis, 12 of the 32 genes related to muscular dysfunction (NEB, PLEC, XIRP2, TTN, CACNA1D, CMYA5, FAT1, HSPG2, MYH7B, NRAP, OBSCN, SYNE2) have also been reported of association with cardiomyopathy according to the HGMD professional dataset 25 2021.1 release. Four of the 12 genes (NEB, PLEC, XIRP2, TTN) and 9 other genes (ARID1B, CACNA1A, CELSR1, KMT2C, LRP2, AHNAK, COL7A1, LAMA5, RYR1) are also related to congenital heart disease. For instance, the TTN gene encodes the giant muscle filament titin of striated muscle. TTN is associated with familial hypertrophic cardiomyopathy86 and familial dilated cardiomyopathy87, as well as a specific form of cardiomyopathy characterized by arrhythmia, i.e. arrhythmogenic right ventricular cardiomyopathy (ARVC)88. MYH7B encodes the major contractile protein in heart and vascular smooth muscle and is directly involved in muscle contraction89. These findings highlight a subset of POTS patients with rare coding variants from genes related to inherited cardiomyopathy, congenital heart defects, or congenital channelopathy (e.g. RYR190, CACNA1D91). The POTS symptoms in these patients may be attributed to cardiac insufficiency resulting from genetic mutations, without necessarily involving subclinical or inconspicuous structural or functional changes. 2.1.6 Psychiatric and Neurodevelopmental Disorders in POTS It's not uncommon for patients with POTS to experience psychological issues like depression and anxiety92. There is a potential bidirectional relationship between POTS and psychological distress, whereas the exact role of psychiatric and psychological factors in the development of POTS remains a topic of ongoing research. From the 55 genes we identified, 4 have been linked to anxiety disorder, 8 to schizophrenia, and 4 to autism spectrum disorder (ASD) (the GWAS catalog https://www.ebi.ac.uk , accessed on Sep 5, 2021). As per HGMD, 14 genes are linked to schizophrenia, and notably, 43 out of the 55 genes are related to ASD (Supplementary Table 5). Autonomic dysfunction is common in ASD 93. The findings of our study imply that individuals diagnosed with POTS may also have concurrent atypical psychiatric or neurodevelopmental disorders. Owens et al. have documented a correlation between dysautonomia and ASD94. Moreover, in clinical settings, we have observed a number of POTS patients with ASD. 2.2 Insights gained by ClinVar P/LP variants In our WES study, we identified 92 heterozygous P/LP variants in 87 different genes classified by ClinVar. Many of these genes are associated with autosomal recessive predisposition; therefore, patients do not typically manifest obvious genetic syndromes when these variants are present in a heterozygous state. Among these genes, the otogelin gene (OTOG) has also been identified in the gene-based GWAS study on common genetic variants. OTOG encodes a protein that is primarily associated with the acellular membranes of the inner ear and plays a crucial role in auditory and vestibular functions 95. The LP variant NP_001278992.1:p.Gly2238Ser causes a rare genetic deafness with autosomal recessive inheritance (https://www.ncbi.nlm.nih.gov/clinvar/variation/930161/). While OTOG is primarily All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint associated with the inner ear, there is some evidence to suggest that ANS dysfunction can be linked to inner ear disorders96. Disruptions in the vestibular system can lead to balance and coordination problems, which may indirectly affect ANS regulation in some individuals. Furthermore, several intriguing genes offer additional insights into the pathogenesis of POTS. 2.2.1 P/LP variants with Dominant effects Among the 92 heterozygous P/LP variants, 3 have been reported of dominant genetic effects, including USP48 (ubiquitin specific peptidase 48)/NP_115612.4:p.Gly406Arg causing Deafness, autosomal dominant 85; CAPN3 (calpain 3)/NP_000061.1:p.Arg490Trp causing Muscular dystrophy, limb-girdle, autosomal dominant 4; POLG (DNA polymerase gamma, catalytic subunit)/NP_002684.1:p.Trp748Ser causing Progressive external ophthalmoplegia with mitochondrial DNA deletions, autosomal dominant 1. The co-occurrence of these P/LP variants with POTS could be coincidental. However, CAPN3 encodes a muscle-specific component of the calpain protease, which is a muscle-specific member of the calpain large subunit family, and exhibiting a specific binding affinity for the protein titin 97. The variant causing muscular dystrophy can lead to muscle weakness and mobility issues, contributing to POTS by promoting deconditioning and muscle pump dysfunction. POLG encodes the catalytic subunit of mitochondrial DNA polymerase, a critical enzyme responsible for replicating mitochondrial DNA98. POLG plays a pivotal role in maintaining the integrity and proper functioning of mitochondrial DNA, which is essential for the production of energy within cells. Mitochondrial dysfunction can affect multiple physiological processes, including those related to the autonomic nervous system and cardiovascular regulation, thus may contribute to POTS 99. Besides these P/LP variants, the myosin heavy chain 7 (MYH7, related to hypertrophic cardiomyopathy) variant NP_000248.2:p.Arg787Cys at exon21 is classified as DM by HGMD and Likely pathogenic by InterVar, but with Conflicting interpretations of pathogenicity by ClinVar. MYH7 encodes the beta (or slow) heavy chain subunit of cardiac myosin. This specific heavy chain is primarily expressed in the normal human ventricle, as well as in skeletal muscle tissues rich in slow-twitch type I muscle fibers 100. Its mutation can affect myocardial contractility. 2.2.2 Insights gained from enriched gene sets with P/LP variants ORA analysis of the 87 genes with P/LP variants identified several gene sets of statistical significance. Significant DisGeNET gene sets include Hepatomegaly (C0019209), Epilepsy (C0014544), Cerebellar Ataxia (C0007758), Seizures (C0036572), Failure to gain weight (C0231246), Pediatric failure to thrive (C2315100), Comatose (C0009421), Vomiting (C0042963), Muscle hypotonia (C0026827). Hepatomegaly may be related to splanchnic redistribution of blood, contributing to thoracic hypovolemia in POTS. Epilepsy and seizures often cause autonomic nervous system dysfunction 101. Cerebellar ataxia, affecting balance and coordination, may contribute to orthostatic intolenrance in POTS. Moreover, the association of POTS with gene sets linked to clinical diagnoses such as coma might suggest that certain genetic mutations have a profound impact on neurological functions. Muscle hypotonia can contribute to POTS by promoting deconditioning and muscle pump dysfunction. Gene sets of GO Cellular Component include mitochondrial matrix (GO:0005759), and apical part of cell (GO:0045177). Dysfunction in the mitochondrial matrix can lead to energy deficits, which are implicated in dysautonomia and may impact muscle function, including the All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint heart and vascular system, thus contribute to POTS99. The apical part of a cell is important in cellular polarization and signaling102. In endothelial cells, dysfunction in the apical part could affect vascular tone and blood flow regulation. Gene sets of GO Molecular Function include hydrolase activity, acting on glycosyl bonds (GO:0016798), transferase activity, transferring glycosyl groups (GO:0016757), oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen (GO:0016705). Hydrolases that act on glycosyl bonds are involved in the breakdown of carbohydrates and glycoproteins 103. Impaired carbohydrate metabolism could affect energy availability, potentially influencing the energy-dependent processes of the autonomic nervous system. Glycoproteins play roles in cell signaling and immune responses104. Abnormalities in glycoprotein breakdown could contribute to dysregulated immune responses, potentially relevant in autoimmune etiologies of POTS. Glycosylation is important in cell signaling and immune function 105. Aberrations here could contribute to autoimmune responses or dysregulation of the autonomic nervous system, both implicated in POTS. Oxidoreductase enzymes play a central role in oxidative phosphorylation and energy production in cells, and are closely related to mitochondrial function. These enzymes also play roles in oxidative stress, which has been implicated in various pathologies, including inflammation and autoimmunity.

and perspective Leveraging our expertise in omics and the analysis of heterogeneous phenotypes, this study marks an important step forward in understanding the complex etiologies of POTS, a condition with significant phenotypic heterogeneity and elusive genetic underpinnings. With convincing statistical significance, we have illuminated the role of both common and rare genetic variants in POTS development. We have identified several gene sets through GWAS, notably linked to cell- cell junctions, synaptic membranes, transporter complexes, and early estrogen responses. Our WES analysis brings into focus specific genes and molecular mechanisms including muscular and microtubule dysfunction, autonomic nervous system regulation, and mitochondrial activity. This enhanced genetic understanding opens new avenues for developing personalized treatment strategies, tailored to the unique genetic makeup of individual POTS patients. Meanwhile, the study's findings regarding the relationship between POTS-related genes and psychiatric and neurodevelopmental disorders underscore the importance of addressing psychological aspects in the management of POTS. The burden analysis of VOIs in the WES study identified 55 genes with statistical significance and 87 genes with P/LP variants (including 3 genes with dominant genetic variants). Due to the limitations imposed by the sample size and phenotypic heterogeneity, the GWAS study achieved statistical significance for several gene sets rather than for individual genes. Nonetheless, common variants from several plausible candidate genes might exert regulatory effects as modifiers in the pathophysiology of POTS and merit further investigation. For instance, common variants in the glycoprotein alpha-galactosyltransferase 1 gene (GGTA1), the 3-oxoacid CoA-transferase 2 gene (OXCT2), and the 3-oxoacid CoA-transferase 2 pseudogene 1 gene (OXCT2P1), have shown nominal statistical significance in association with POTS. These variants are linked to gene expression in the heart atrial appendage, as per the Genotype-Tissue Expression (GTEx) project data (https://www.gtexportal.org/ )106 (Supplementary Table 6), implying a direct role in heart rate regulation107, a key aspect of POTS pathogenesis. The genetic All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint insights not only enhance our knowledge of POTS pathogenesis but also hold promise for developing more effective, individualized treatment strategies, ultimately improving patient outcomes in this challenging and multifaceted condition. Declarations Ethics approval and consent to participate Informed consent was obtained from all subjects or, if subjects are under 18, from a parent and/or legal guardian with assent from the child if 7 years or older. The Institutional Review Board (IRB) of CHOP approved this study. Consent for publication Not applicable. Availability of data and material The data that support the findings of this study are available on request from the corresponding author. Competing interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding This study was funded in part by donation from the Esther Feigenbaum Foundation, The Siemer Family Foundation, by an Endowed Chair in Genomic Research (HH) and by an Institutional Development Award to the Center for Applied Genomics from The Children’s Hospital of Philadelphia.

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The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint Table 1 Comorbidities with POTS Cohort Comorbidities Number of patients The family cohort (case n=114) Ehlers–Danlos Syndrome (EDS) 11 EDS + autoimmune alopecia 1 Mast cell activation syndrome (MCAS) 1 MCAS + Wolff-Parkinson-White syndrome + Leigh disease 1 Scoliosis+ Hashimoto's thyroiditis + benign premature atrial contractions 1 Crohn's disease 1 Post concussion 1 Benign Rolandic epilepsy 1 The Case Control cohort (case n=207) EDS 6 EDS + eosinophilic esophagitis 1 EDS + Gilbert syndrome 1 EDS + IgA deficiency 1 EDS + MCAS 1 EDS + Chiari malformation + exercise-induced asthma + Asperger syndrome + gastroesophageal reflux + urticaria + and left duplicated ureter 1 Multiple sclerosis 2 MCAS 1 Crohn's disease 1 Alport's syndrome 1 Asperger syndrome + seizure disorder 1 Beh /i1et's disease 1 Post concussion 1 Hodgkin lymphoma 1 Type 1 diabetes 1 Neuromuscular disorder 1 Congenital adrenal hyperplasia + von Willebrand's disease + Hashimoto's disease 1 UTI + VUR + asthma + vitamin D insufficiency + Lyme disease 1 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint Table 2 Over-representation analysis of the 716 genes showed nominal significance in both the family cohort and the case- control cohort a. By Geneontology Cellular Component Gene Set Description P Value FDR Genes GO:0005911 cell-cell junction 4.34E- 06 0.0007 47 AJAP1, ANK3, APP, ATP2A2, BAIAP2L2, CD2AP, CDH13, CDH15, CDH22, CDH4, CDH8, CNN3, CNTNAP2, COL13A1, CTNNA3, DSG1, EPB41L3, F11R, FBF1, FRMD4A, GRB2, KIFC3, LYN, NCK1, NDRG1, NFASC, PAK4, PDZD2, PKP4, PPL, PRKCZ, SLC2A1, TJP2, TJP3, UBN1, VASP, WASF2 GO:0097060 synaptic membrane 1.54E- 05 0.0013 27 ANK3, ANKS1B, ATP2B2, ATP2B4, CADPS2, CDH8, CHRNA3, CHRNA4, CNR1, CNTN1, COL13A1, CPEB1, DENND1A, DGKI, DISC1, DLG2, DLGAP1, GABRG3, GRIK4, KCNB1, KCNC1, KCNJ3, LRRC4C, LRRTM4, NTRK3, PI4K2A, ROGDI, SEMA4F, SHC4, SHISA6, SLC1A6, SLC8A3, SYNJ2BP, SYT6, UNC13C GO:0043025 neuronal cell body 8.58E- 05 0.0049 21 ADA, ADAM21, ADCY10, APP, ASIC2, BRD1, CACNA1B, CHRNA3, CHRNA4, CNN3, CNTNAP2, COBL, CRHBP, CYGB, DAB2IP, DENND1A, DGKI, FZD3, GIP, KCNB1, KCNC1, KCNN3, KNDC1, LRP8, MBP, MYO1D, NMNAT3, NPTXR, PCP2, PDE9A, PI4K2A, PRKCZ, RBFOX3, ROGDI, SLC8A3, TGFB2 GO:0031252 cell leading edge 0.0002 01 0.0086 47 ABLIM1, AIF1L, APBB2, APP, CD2AP, CNTNAP2, COBL, CTNNA3, CUBN, EPB41L3, FERMT1, FGD2, GABRG3, IQGAP2, JMY, KCNB1, KCNC1, MACF1, MYO1D, MYO1G, PDE9A, PIEZO1, PRKCZ, SHISA6, SNTG1, SRC, SYNE2, TPM1, VASP, WASF2 GO:1990351 transporter complex 0.0003 6 0.0124 01 ANO2, CACNA1B, CACNA1E, CACNA2D4, CALM1, CATSPERB, CHRNA3, CHRNA4, CNGB1, CNTNAP2, CUBN, DLG2, DPP10, DPP6, GABRG3, GRIK4, KCNB1, KCNC1, KCNJ3, KCNJ6, KCNK6, RYR2, SCN8A, SHISA6, SYNJ2BP, TTYH1 GO:0031253 cell projection membrane 0.0009 42 0.027 AIF1L, CNGA1, CNGB1, CNTNAP2, CUBN, EPB41L3, EPS15, EVC, FERMT1, FGD2, GABRG3, GUCY2D, KCNB1, KCNC1, MACF1, MYO1D, PDE9A, PIEZO1, SHISA6, SNTG1, SRC, SYNE2, TPM1, TTYH1, VASP All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint GO:0098984 neuron to neuron synapse 0.0025 93 0.0637 02 ANKS1B, ARFGEF2, ATP2B2, CHRNA3, CNN3, CPEB1, DGKI, DISC1, DLG2, DLGAP1, EPB41L3, GRIK4, LRP8, LRRC4C, LYN, NCK2, PKP4, PRKAR1B, PRKCZ, SHISA6, SRC, SYNJ2BP, SYT9, TANC2 GO:0005875 microtubule associated complex 0.0040 53 0.0801 83 CHURC1-FNTB, DNAH1, DNAH12, DNAH2, DNAH3, DNAH7, DNAH8, DNAH9, KIF15, KIFC1, KIFC3, LRP8, WDR78 GO:0033267 axon part 0.0041 96 0.0801 83 ADCY10, ANK3, APBB2, APP, AUTS2, CALM1, CDH8, CNGB1, CNR1, CNTNAP2, COBL, CRHBP, DGKI, DLG2, EPB41L3, IQCJ-SCHIP1, KCNC1, MBP, MYO1D, NFASC, NPTXR, PRKCZ, PTPRN2, SCN8A, UNC13C b. By Geneontology Mulecular Function Gene Set Description P Value FDR Genes GO:0050839 cell adhesion molecule binding 4.81E- 06 0.0013 55 ANK3, CD2AP, CDH13, CDH15, CDH22, CDH4, CDH8, CNN3, COL5A1, CTNNA3, CXCL12, DAB2IP, ECM2, EGFR, EPS15, F11R, FRMD5, GAPVD1, LRRC4C, LYN, MACF1, NCK1, NDRG1, NRXN3, PAK4, PARVA, PFKP, PKP4, PPL, PRKCA, PTPRT, SRC, STAT1, TENM4, TJP2, TMPO, VASP, WASF2 GO:0045503 dynein light chain binding 2.18E- 05 0.0030 74 DNAH1, DNAH2, DNAH3, DNAH7, DNAH8, DNAH9, WDR78 GO:0003779 actin binding 6E-05 0.0055 6 ABLIM1, ABLIM2, AIF1L, CNN3, COBL, CORO2B, COTL1, CTNNA3, DSTN, EGFR, EPB41L3, FERMT1, GAS7, IQGAP2, JMY, MACF1, MYO1D, MYO1F, MYO1G, MYPN, MYRIP, PACRG, PARVA, PHACTR1, SNTB2, SNTG1, SVIL, SYNE2, TPM1, TRIOBP, VASP, WASF2 GO:0045505 dynein intermediate chain binding 7.89E- 05 0.0055 6 BICD1, DNAH1, DNAH2, DNAH3, DNAH7, DNAH8, DNAH9 GO:0003774 motor activity 0.0003 95 0.0222 66 DNAH1, DNAH12, DNAH2, DNAH3, DNAH7, DNAH8, DNAH9, KIF15, KIFC1, KIFC3, MYO1D, MYO1F, MYO1G, WDR78 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint GO:0051959 dynein light intermediate chain binding 0.0005 2 0.0244 56 DNAH1, DNAH2, DNAH3, DNAH7, DNAH8, DNAH9 GO:0046873 metal ion transmembr ane transporter activity 0.0014 59 0.0587 74 ASIC2, ATP2A2, ATP2B2, ATP2B4, CACNA1B, CACNA1E, CACNA2D4, CNR1, GRIK4, KCNB1, KCNC1, KCNJ3, KCNJ6, KCNK6, KCNN3, RYR2, SCN8A, SLC1A6, SLC1A7, SLC23A2, SLC24A2, SLC24A3, SLC24A4, SLC28A1, SLC39A10, SLC41A2, SLC4A5, SLC8A3, TTYH1 GO:0005516 calmodulin binding 0.0017 3 0.0609 86 ATP2B2, ATP2B4, CNN3, EGFR, IQGAP2, KCNN3, MBP, MYO1D, MYO1F, MYO1G, PLA2G6, RYR2, SLC8A3, SNTB2, SPATA17, UNC13C GO:0046875 ephrin receptor binding 0.0025 86 0.0810 12 ANKS1B, GRB2, LYN, NCK1, SRC c. By Hallmark Gene Set Description P Value FDR Genes HALLMARK_ESTROGEN_RESPONSE_ EARLY early estrogen response 3.78E- 04 0.0188 89 ABLIM1, ADCY9, CELSR1, CXCL12, FHL2, GAB2, IGF1R, MPPED2, RAB31, SEC14L2, SLC24A3, SLC27A2, SLC2A1, SLC7A5, SVIL, TJP3, TTC39A d. By the DisGeNET approach Gene Set Description P Value FDR Genes C0236969 Substance- Related Disorders 1.02E- 08 3.7E- 05 ABLIM1, ADARB2, AGBL4, CADPS2, CDCP1, CDH13, CNR1, CSMD3, CTNNA3, DNAH8, FHIT, FRMD4A, MACROD2, NRXN3, PARVA, PRKCH, RAD51B, SLC2A13, SLC45A2, ZNF366 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint Table 3 The 55 Genes showed genome-wide significance by burden analysis of rare coding variants #GENE CASE_COUNT _HET CASE_COUN T_CH CASE_COUNT_ HOM Control_COUNT _HET Control_COUN T_CH Control_COUNT _HOM P_DOM ABCA13 10 2 0 26 7 0 6.40E-08 CELSR1 5 0 0 2 0 0 5.11E-07 DAB2IP 8 0 0 8 0 0 6.50E-09 DNAH1 9 0 0 20 0 0 1.05E-07 DNAH2 7 0 0 13 0 0 1.21E-06 DNAH3 9 1 0 25 4 1 6.37E-07 SYNE2 7 0 0 14 0 0 1.77E-06 ABCA7 7 1 0 8 6 0 1.14E-07 AGRN 6 0 0 5 0 0 3.05E-07 AHNAK 8 2 0 21 0 0 1.56E-06 AP5Z1 5 0 0 3 0 0 1.33E-06 ARHGA P22 4 0 0 0 0 0 8.64E-07 ARID1B 5 0 0 3 0 0 1.33E-06 BAHCC 1 9 0 0 5 0 0 3.08E-11 CACNA 1A 5 1 0 3 1 0 1.33E-06 CACNA 1D 6 0 0 8 0 0 1.84E-06 CFAP46 6 0 0 6 0 0 5.95E-07 CILP 4 0 0 0 0 0 8.64E-07 CMYA5 4 0 0 0 0 0 8.64E-07 COL12A 1 5 0 0 2 0 0 5.11E-07 COL27A 1 6 0 0 5 0 0 3.05E-07 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint COL7A1 8 0 0 9 0 0 1.20E-08 CSMD1 6 0 0 6 0 0 5.95E-07 DNAH1 0 7 0 0 5 0 0 1.51E-08 EPHB4 5 0 0 1 0 0 1.50E-07 FAT1 6 0 0 8 0 0 1.84E-06 FBXW5 6 2 0 2 1 0 1.99E-08 FIGNL1 6 0 0 7 0 0 1.08E-06 FLG 7 0 0 5 0 0 1.51E-08 HSPG2 11 1 0 25 0 0 4.29E-09 KMT2C 8 0 0 8 0 0 6.50E-09 KNTC1 5 0 0 2 0 0 5.11E-07 LAMA5 13 1 0 21 0 0 5.38E-12 LRP2 11 0 0 11 0 0 7.17E-12 MUC16 14 2 0 25 0 0 2.11E-12 MYH7B 5 0 0 2 0 0 5.11E-07 NEB 12 3 0 21 1 0 7.64E-11 NRAP 5 0 0 3 0 0 1.33E-06 NUP160 4 0 0 0 0 0 8.64E-07 OBSCN 11 1 0 14 0 0 4.20E-11 PABPC1 L 4 0 0 0 0 0 8.64E-07 PKD1 7 1 0 4 0 0 6.46E-09 PKD1L2 8 1 0 19 10 2 1.56E-06 PKHD1 L1 7 0 0 9 0 0 1.97E-07 PLEC 11 1 0 21 0 0 1.02E-09 PLXNA2 4 0 0 0 0 0 8.64E-07 RP1L1 6 0 0 8 1 0 1.84E-06 RYR1 8 0 0 5 0 0 7.02E-10 SACS 8 0 0 4 0 0 2.77E-10 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint SRRM2 5 0 0 2 0 0 5.11E-07 TG 6 0 0 5 0 0 3.05E-07 TTN 24 5 0 51 1 0 1.72E-19 USH2A 9 0 0 9 0 0 6.76E-10 XIRP2 6 0 0 7 0 0 1.08E-06 ZFHX3 6 0 0 6 0 0 5.95E-07 Abbreviations: HET, heterozygote; CH, compound heterozygote; HOM, homozygote; P_dom, P value of dominant model; P_rec, P value of recessive model. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint Table 4 Over-representation analysis of the 55 genes burdened with VOIs a. By the DisGeNET approach Gene Set Description P Value FDR Genes C1864711 Muscle biopsy shows dystrophic changes 2.41E-05 0.045614 PLEC, RYR1, SYNE2, TTN C0026850 Muscular Dystrophy 3.92E-05 0.045614 PLEC, RYR1, SYNE2, TTN C0221629 Proximal muscle weakness 5.55E-05 0.045614 NEB, RYR1, SYNE2, TTN C1838869 Proximal neurogenic muscle weakness 5.55E-05 0.045614 NEB, RYR1, SYNE2, TTN C0746674 Generalized muscle weakness 0.000109 0.045614 NEB, PLEC, RYR1, TTN C0151576 Elevated creatine kinase 0.000113 0.045614 HSPG2, PLEC, RYR1, SYNE2, TTN C0241005 Creatine phosphokinase serum increased 0.000113 0.045614 HSPG2, PLEC, RYR1, SYNE2, TTN C0376175 Bell Palsy 0.000117 0.045614 COL12A1, NEB, RYR1, TTN C1858719 Facial muscle weakness of muscles innervated by CN VII 0.000117 0.045614 COL12A1, NEB, RYR1, TTN C0427055 Facial Paresis 0.000125 0.045614 COL12A1, NEB, RYR1, TTN b. By Geneontology Cellular Component Gene Set Description P Value FDR Genes GO:0043292 contractile fiber 3.00E-10 5.16E-08 AHNAK, CACNA1D, CMYA5, MYH7B, NEB, NRAP, OBSCN, PLEC, RYR1, SYNE2, TTN, XIRP2 GO:0042383 sarcolemma 3.78E-04 0.018834 AHNAK, CACNA1D, OBSCN, PLEC, RYR1 GO:0031012 extracellular matrix 4.02E-04 0.018834 AGRN, CILP, COL12A1, COL27A1, COL7A1, FLG, HSPG2, LAMA5, USH2A GO:0016528 sarcoplasm 4.38E-04 0.018834 CMYA5, PLEC, RYR1, SYNE2 GO:0030055 cell-substrate junction 5.55E-04 0.019084 AHNAK, ARHGAP22, FAT1, HSPG2, NRAP, PLEC, SYNE2, XIRP2 c. By Geneontology Mulecular Function Gene Set Description P Value FDR Genes All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint GO:0005201 ex tracellular matrix structural constituent 9.23E-07 0.000197 AGRN, CILP, COL12A1, COL27A1, COL7A1, HSPG2, LAMA5 GO:0045503 dynein light chain binding 1.40E-06 0.000197 DNAH1, DNAH10, DNAH2, DNAH3 GO:0051959 dynein light intermediate chain binding 2.60E-06 0.000211 DNAH1, DNAH10, DNAH2, DNAH3 GO:0045505 dynein intermediate chain binding 3.00E-06 0.000211 DNAH1, DNAH10, DNAH2, DNAH3 GO:0042805 actinin binding 8.80E-06 0.000496 CACNA1D, NRAP, TTN, XIRP2 GO:0008307 structural constituent of muscle 1.43E-05 0.000674 NEB, OBSCN, PLEC, TTN GO:0030506 ankyrin binding 4.03E-05 0.001624 CACNA1D, OBSCN, PLEC GO:0003774 motor activity 9E-05 0.003173 DNAH1, DNAH10, DNAH2, DNAH3, MYH7B GO:0003779 actin binding 0.000481 0.01508 MYH7B, NEB, NRAP, PLEC, SYNE2, TTN, XIRP2 GO:0016887 ATPase activity 0.000627 0.017687 ABCA13, ABCA7, DNAH1, DNAH10, DNAH2, DNAH3, FIGNL1 d. By Hallmark Gene Set Description P Value FDR Genes None e. By Human Phenotype Ontology Gene Set Description P Value FDR Genes HP:0003306 Spinal rigidity 4.94E-07 0.002311 AGRN, COL12A1, HSPG2, NEB, SYNE2, TTN HP:0003458 EMG: myopathic abnormalities 3E-05 0.034381 AGRN, COL12A1, NEB, RYR1, SYNE2, TTN HP:0003457 EMG abnormality 3.84E-05 0.034381 AGRN, CACNA1D, COL12A1, HSPG2, NEB, RYR1, SYNE2, TTN HP:0003701 Proximal muscle weakness 0.000042 0.034381 AGRN, COL12A1, NEB, PLEC, RYR1, SYNE2, TTN HP:0100285 EMG: impaired neuromuscular transmission 4.27E-05 0.034381 AGRN, CACNA1D, RYR1, TTN HP:0003324 Generalized muscle weakness 4.41E-05 0.034381 AGRN, COL12A1, NEB, PLEC, RYR1, TTN All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint HP:0003236 Elevated serum creatine phosphokinase 6.24E-05 0.03722 AP5Z1, COL12A1, HSPG2, NEB, PLEC, RYR1, SYNE2, TTN HP:0003690 Limb muscle weakness 6.48E-05 0.03722 AGRN, AP5Z1, NEB, RYR1, SACS, SYNE2, TTN HP:0040081 Abnormal levels of creatine kinase in blood 7.72E-05 0.03722 AP5Z1, COL12A1, HSPG2, NEB, PLEC, RYR1, SYNE2, TTN HP:0011021 Abnormality of circulating enzyme level 7.96E-05 0.03722 AP5Z1, COL12A1, HSPG2, NEB, PLEC, RYR1, SYNE2, TTN All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint Table 5 Over-representation analysis of the 87 genes with P/LP variants a. By the DisGeNET approach Gene Set Description P Value FDR Genes C4020899 Autosomal recessive predisposition <2.2e- 16 <2.2e- 16 ABCA4, ABCC6, ABCC8, ADSL, ALDOB, APRT, ASL, ASS1, ATM, BLM, BTD, C6, CAPN3, CBLIF, CFTR, COQ4, CTSA, DARS2, DBT, DPM1, FANCI, FASTKD2, FMO3, GAA, GALT, GBA, GBE1, GGCX, GYS2, ITGA2B, LAMB3, LIPT1, MC2R, MUTYH, PAH, PCCB, PDE6B, PEPD, PEX5, PLOD1, PMS2, POLG, POLR3A, POMT1, PRF1, PROM1, RAD50, RPE65, RYR1, SLC12A3, SLC17A5, SLC3A1, TG, TNFRSF13B, TRMU, TSFM, TYR, USH2A C0019209 Hepatomegaly 4.70E- 12 8.56E- 09 ABCC8, ALDOB, ASL, ASS1, BTD, DPM1, FASTKD2, GAA, GALT, GBA, PCCB, PEPD, PEX5, POLG, PRF1, SLC17A5, TNFRSF13B, TRMU, TSFM C0014544 Epilepsy 1.14E- 11 1.38E- 08 ABCC8, ADSL, ALDOB, ASL, ASS1, ATM, BTD, CTSA, DBT, DPM1, FASTKD2, GBA, GYS2, MC2R, PAH, PCCB, PEX5, PMS2, POLG, POMT1, PRF1, RPE65, SLC12A3, SLC17A5, SLC3A1, TSFM C0007758 Cerebellar Ataxia 2.25E- 11 2.05E- 08 ABCC8, ASL, ASS1, ATM, BTD, DARS2, DBT, DPM1, FASTKD2, GBA, HEXB, PEX5, POLG, POLR3A, PRF1, RAD50, SLC17A5, TSFM C0036572 Seizures 5.23E- 11 3.81E- 08 ABCC8, ADSL, ALDOB, ASL, ASS1, ATM, BTD, CTSA, DBT, DPM1, FASTKD2, GBA, GYS2, MC2R, PAH, PCCB, PEX5, PMS2, POLG, POMT1, PRF1, RPE65, SLC12A3, SLC17A5, SLC3A1, TSFM C0231246 Failure to gain weight 1.93E- 09 1E-06 ABCC8, ALDOB, ASL, ASS1, CFTR, DPM1, FASTKD2, GALT, GBA, GBE1, LAMB3, MC2R, PCCB, PEX5, POLG, PRF1, RYR1, SLC17A5, SLC3A1 C2315100 Pediatric failure to thrive 1.93E- 09 1E-06 ABCC8, ALDOB, ASL, ASS1, CFTR, DPM1, FASTKD2, GALT, GBA, GBE1, LAMB3, MC2R, PCCB, PEX5, POLG, PRF1, RYR1, SLC17A5, SLC3A1 C0009421 Comatose 3.45E- 09 1.57E- 06 ABCC8, ALDOB, ASL, ASS1, DBT, MC2R, PCCB, POLG, PRF1 C0042963 Vomiting 1.34E- 08 5.42E- 06 ABCC8, ALDOB, ASL, ASS1, BTD, DBT, GALT, HSD3B2, PCCB, POLG, TRMU All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint C0026827 Muscle hypotonia 2.36E- 08 8.59E- 06 ADSL, AR, BTD, COQ4, DBT, DPM1, FASTKD2, GAA, GBA, GBE1, PEX5, PLOD1, PMS2, POLG, POMT1, PRF1, RPE65, RYR1, SLC17A5, SLC3A1, TG, TRMU b. By Geneontology Cellular Component Gene Set Description P Value FDR Genes GO:0005759 mitochondrial matrix 3.56E- 04 0.061 BTD, DARS2, DBT, FASTKD2, LIPT1, MCCC2, PCCB, POLG, TARS2, TSFM GO:0045177 apical part of cell 1.60E- 03 0.099 ABCC6, CBLIF, CFTR, OTOG, PROM1, SLC12A3, SLC34A3, USH2A GO:0009295 nucleoid 2.09E- 03 0.099 DBT, FASTKD2, POLG GO:0005774 vacuolar membrane 2.30E- 03 0.099 ABCC6, CFTR, CTSA, GAA, GBA, HLA-DRB1, SLC17A5, SLC3A1 c. By Geneontology Mulecular Function Gene Set Description P Value FDR Genes GO:0016798 hydrolase activity, acting on glycosyl bonds 8.07E- 06 0.002 CTSA, GAA, GBA, GBE1, HEXB, MUTYH, OTOG GO:0016757 transferase activity, transferring glycosyl groups 5.45E- 05 0.008 ALG1, APRT, DPM1, FUT1, GBE1, GYS2, HEXB, PLOD1, POMT1 GO:0016705 oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen 4.37E- 04 0.041 CYP4F22, FMO3, P3H1, PAH, PLOD1, TYR d. By Hallmark Gene Set Description P Value FDR Genes None e. By Human Phenotype Ontology Gene Set Description P Value FDR Genes All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint HP:0001939 Abnormality of metabolism/homeostasis 3.60E- 08 1.68E- 04 ABCA4, ABCC6, ABCC8, ALDOB, ALG1, APRT, AR, ASL, ASS1, ATM, BLM, BTD, CAPN3, CBLIF, CFTR, COQ4, CTSA, CYP4F22, DBT, DCTN1, DHDDS, DPM1, FANCI, FASTKD2, FMO3, GAA, GALT, GBA, GBE1, GYS2, HEXB, HLA-DRB1, HSD3B2, IL17RC, LAMB3, LIPT1, MC2R, MCCC2, MUTYH, PAH, PCCB, PDE6B, PEPD, PEX5, PLOD1, PMS2, POLG, POMT1, PRF1, PROM1, RAD50, RPE65, RYR1, SLC12A3, SLC17A5, SLC34A3, SLC3A1, TARS2, TNFRSF13B, TRMU, TSFM, USH2A HP:0004360 Abnormality of acid-base homeostasis 1.64E- 07 2.87E- 04 ABCC8, ALDOB, ASL, ASS1, BTD, COQ4, DBT, FASTKD2, GALT, GYS2, HSD3B2, LIPT1, MCCC2, PAH, PCCB, POLG, RYR1, SLC12A3, SLC3A1, TARS2, TRMU, TSFM HP:0001438 Abnormality of abdomen morphology 1.84E- 07 2.87E- 04 ABCC8, ALDOB, ALG1, ASL, ASS1, ATM, BTD, CFTR, CTSA, DHDDS, DPM1, FASTKD2, FMO3, GAA, GALT, GBA, GBE1, HEXB, HLA-DRB1, PCCB, PEPD, PEX5, PMS2, POLG, PRF1, SLC17A5, SLC34A3, TNFRSF13B, TRMU, TSFM HP:0001941 Acidosis 2.55E- 07 2.94E- 04 ABCC8, ALDOB, ASL, ASS1, BTD, COQ4, DBT, FASTKD2, GALT, GYS2, HSD3B2, LIPT1, MCCC2, PAH, PCCB, POLG, RYR1, SLC3A1, TARS2, TRMU, TSFM HP:0003271 Visceromegaly 3.14E- 07 2.94E- 04 ABCC8, ALDOB, ALG1, ASL, ASS1, ATM, BTD, CFTR, CTSA, DHDDS, DPM1, FASTKD2, FMO3, GAA, GALT, GBA, GBE1, HEXB, HLA-DRB1, PCCB, PEPD, PEX5, POLG, PRF1, SLC17A5, TNFRSF13B, TRMU, TSFM HP:0410042 Abnormal liver morphology 1.64E- 06 1.28E- 03 ABCC8, ALDOB, ALG1, ASL, ASS1, ATM, BTD, CFTR, CTSA, DHDDS, DPM1, FASTKD2, GAA, GALT, GBA, GBE1, GYS2, HEXB, HLA-DRB1, IL17RC, LIPT1, PCCB, PEPD, PEX5, POLG, PRF1, SLC17A5, TARS2, TNFRSF13B, TRMU, TSFM HP:0001259 Coma 2.25E- 06 1.46E- 03 ABCC8, ALDOB, ASL, ASS1, BTD, DBT, MC2R, MCCC2, PCCB, POLG, PRF1 HP:0002240 Hepatomegaly 2.61E- 06 1.46E- 03 ABCC8, ALDOB, ALG1, ASL, ASS1, BTD, CFTR, DHDDS, DPM1, FASTKD2, GAA, GALT, GBA, HLA-DRB1, PCCB, PEPD, PEX5, POLG, PRF1, SLC17A5, TNFRSF13B, TRMU, TSFM All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint HP:0002012 Abnormality of the abdominal organs 2.80E- 06 1.46E- 03 ABCC8, ALDOB, ALG1, ASL, ASS1, ATM, BTD, CFTR, CTSA, DBT, DHDDS, DPM1, FANCI, FASTKD2, FMO3, GAA, GALT, GBA, GBE1, GYS2, HEXB, HLA-DRB1, IL17RC, LIPT1, MMP21, PCCB, PEPD, PEX5, PMS2, POLG, PRF1, RAD50, SLC17A5, TARS2, TG, TNFRSF13B, TRMU, TSFM HP:0001392 Abnormality of the liver 5.14E- 06 2.37E- 03 ABCC8, ALDOB, ALG1, ASL, ASS1, ATM, BTD, CFTR, CTSA, DHDDS, DPM1, FANCI, FASTKD2, GAA, GALT, GBA, GBE1, GYS2, HEXB, HLA-DRB1, IL17RC, LIPT1, PCCB, PEPD, PEX5, PMS2, POLG, PRF1, SLC17A5, TARS2, TG, TNFRSF13B, TRMU, TSFM All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted May 5, 2024. ; https://doi.org/10.1101/2024.05.03.24306814doi: medRxiv preprint