Faculty Bibliography

BACKGROUND:Cross-species immunological incompatibilities have hampered pig-to-human xenotransplantation, but porcine genome engineering recently enabled the first successful experiments. However, little is known about the immune response after the transplantation of pig kidneys to human recipients. We aimed to precisely characterise the early immune responses to the xenotransplantation using a multimodal deep phenotyping approach. METHODS:We did a complete phenotyping of two pig kidney xenografts transplanted to decedent humans. We used a multimodal strategy combining morphological evaluation, immunophenotyping (IgM, IgG, C4d, CD68, CD15, NKp46, CD3, CD20, and von Willebrand factor), gene expression profiling, and whole-transcriptome digital spatial profiling and cell deconvolution. Xenografts before implantation, wild-type pig kidney autografts, as well as wild-type, non-transplanted pig kidneys with and without ischaemia-reperfusion were used as controls. FINDINGS:cells. Both xenografts showed increased expression of genes biologically related to a humoral response, including monocyte and macrophage activation, natural killer cell burden, endothelial activation, complement activation, and T-cell development. Whole-transcriptome digital spatial profiling showed that antibody-mediated injury was mainly located in the glomeruli of the xenografts, with significant enrichment of transcripts associated with monocytes, macrophages, neutrophils, and natural killer cells. This phenotype was not observed in control pig kidney autografts or in ischaemia-reperfusion models. INTERPRETATION:Despite favourable short-term outcomes and absence of hyperacute injuries, our findings suggest that antibody-mediated rejection in pig-to-human kidney xenografts might be occurring. Our results suggest specific therapeutic targets towards the humoral arm of rejection to improve xenotransplantation results. FUNDING:OrganX and MSD Avenir.

Genetically modified xenografts are one of the most promising solutions to the discrepancy between the numbers of available human organs for transplantation and potential recipients. To date, a porcine heart has been implanted into only one human recipient. Here, using 10-gene-edited pigs, we transplanted porcine hearts into two brain-dead human recipients and monitored xenograft function, hemodynamics and systemic responses over the course of 66 hours. Although both xenografts demonstrated excellent cardiac function immediately after transplantation and continued to function for the duration of the study, cardiac function declined postoperatively in one case, attributed to a size mismatch between the donor pig and the recipient. For both hearts, we confirmed transgene expression and found no evidence of cellular or antibody-mediated rejection, as assessed using histology, flow cytometry and a cytotoxic crossmatch assay. Moreover, we found no evidence of zoonotic transmission from the donor pigs to the human recipients. While substantial additional work will be needed to advance this technology to human trials, these results indicate that pig-to-human heart xenotransplantation can be performed successfully without hyperacute rejection or zoonosis.

BACKGROUND:Hydrocephalus is a highly heterogeneous multifactorial disease that arises from genetic and environmental factors. Familial genetic studies of hydrocephalus have elucidated four robustly associated hydrocephalus associated loci. This study aims to identify potential genetic causation in cases of hydrocephalus, with or without spina bifida and Dandy Walker Syndrome (DWS), using family-based rare variant association analysis of whole exome sequencing. METHODS:We performed whole exome sequencing in 143 individuals across 48 families where at least one offspring was affected with hydrocephalus (N.=27), with hydrocephalus with spina bifida (N.=21) and with DWS (N.=3), using Illumina HiSeq 2500 instrument. RESULTS:No pathogenic or putative pathogenic single-nucleotide variants were evident in the four known hydrocephalus loci in our subjects. However, after examining 73 known hydrocephalus genes previously identified from literature, we identified three potentially impactful variants from the cohort. Using a gene panel comprising variants in known neural tube defects loci, we identified a total of 1024 potentially deleterious variants, of which 797 were missense variants and 191 were frameshift variants, 36 were stop gain/loss variants. A small portion of our family pedigree analyses yielded putative genetic signals which may be responsible for hydrocephaly elated phenotypes, however the low diagnostic yield may be due to lack of capture of genetic variants in the exonic regions i.e. structural variants may only be evident from whole genome sequencing. CONCLUSIONS:We identified three potentially impactful variants from our cohort in 73 known hydrocephalus genes previously identified in literature.

BACKGROUND:Endomyocardial biopsy (EMB) is currently considered the gold standard for diagnosing cardiac allograft rejection. However, significant limitations related to histological interpretation variability are well-recognized. We sought to develop a methodology to evaluate EMB solely based on gene expression, without relying on histology interpretation. METHODS:Sixty-four EMBs were obtained from 47 post-heart transplant recipients, who were evaluated for allograft rejection. EMBs were subjected to mRNA sequencing, in which an unsupervised classification algorithm was used to identify the molecular signatures that best classified the EMBs. Cytokine and natriuretic peptide peripheral blood profiling was also performed. Subsequently, we performed gene network analysis to identify the gene modules and gene ontology to understand their biological relevance. We correlated our findings with the unsupervised and histological classifications. RESULTS:Our algorithm classifies EMBs into three categories based solely on clusters of gene expression: unsupervised classes 1, 2, and 3. Unsupervised and histological classifications were closely related, with stronger gene module-phenotype correlations for the unsupervised classes. Gene ontology enrichment analysis revealed processes impacting on the regulation of cardiac and mitochondrial function, immune response, and tissue injury response. Significant levels of cytokines and natriuretic peptides were detected following the unsupervised classification. CONCLUSION/CONCLUSIONS:We have developed an unsupervised algorithm that classifies EMBs into three distinct categories, without relying on histology interpretation. These categories were highly correlated with mitochondrial, immune, and tissue injury response. Significant cytokine and natriuretic peptide levels were detected within the unsupervised classification. If further validated, the unsupervised classification could offer a more objective EMB evaluation.

Ischemic stroke represents a significant societal burden across the globe. Rare high penetrant monogenic variants and less pathogenic common single nucleotide polymorphisms (SNPs) have been described as being associated with risk of diseases. Genetic studies in Saudi Arabian patients offer a greater opportunity to detect rare high penetrant mutations enriched in these consanguineous populations. We performed whole exome sequencing on 387 ischemic stroke subjects from Saudi Arabian hospital networks with up to 20,230 controls from the Saudi Human Genome Project and performed gene burden analyses of variants in 177 a priori loci derived from knowledge-driven curation of monogenic and genome-wide association studies of stroke. Using gene-burden analyses, we observed significant associations in numerous loci under autosomal dominant and/or recessive modelling. Stroke subjects with modified Rankin Scale (mRSs) above 3 were found to carry greater cumulative polygenic risk score (PRS) from rare variants in stroke genes (standardized PRS mean > 0) compared to the population average (standardized PRS mean = 0). However, patients with mRS of 3 or lower had lower cumulative genetic risk from rare variants in stroke genes (OR (95%CI) = 1.79 (1.29-2.49), p = 0.0005), with the means of standardized PRS at or lower than 0. In conclusion, gene burden testing in Saudi stroke populations reveals a number of statistically significant signals under different disease inheritance models. However, interestingly, stroke subjects with mRS of 3 or lower had lower cumulative genetic risk from rare variants in stroke genes and therefore, determining the potential mRS cutoffs to use for clinical significance may allow risk stratification of this population.

Background Cardiometabolic diseases are highly comorbid, but their relationship with female-specific or overwhelmingly female-predominant health conditions (breast cancer, endometriosis, pregnancy complications) is understudied. This study aimed to estimate the cross-trait genetic overlap and influence of genetic burden of cardiometabolic traits on health conditions unique to women. Methods and Results Using electronic health record data from 71 008 ancestrally diverse women, we examined relationships between 23 obstetrical/gynecological conditions and 4 cardiometabolic phenotypes (body mass index, coronary artery disease, type 2 diabetes, and hypertension) by performing 4 analyses: (1) cross-trait genetic correlation analyses to compare genetic architecture, (2) polygenic risk score-based association tests to characterize shared genetic effects on disease risk, (3) Mendelian randomization for significant associations to assess cross-trait causal relationships, and (4) chronology analyses to visualize the timeline of events unique to groups of women with high and low genetic burden for cardiometabolic traits and highlight the disease prevalence in risk groups by age. We observed 27 significant associations between cardiometabolic polygenic scores and obstetrical/gynecological conditions (body mass index and endometrial cancer, body mass index and polycystic ovarian syndrome, type 2 diabetes and gestational diabetes, type 2 diabetes and polycystic ovarian syndrome). Mendelian randomization analysis provided additional evidence of independent causal effects. We also identified an inverse association between coronary artery disease and breast cancer. High cardiometabolic polygenic scores were associated with early development of polycystic ovarian syndrome and gestational hypertension. Conclusions We conclude that polygenic susceptibility to cardiometabolic traits is associated with elevated risk of certain female-specific health conditions.

BACKGROUND:Loss-of-Function (LoF) variants in human genes are important due to their impact on clinical phenotypes and frequent occurrence in the genomes of healthy individuals. The association of LoF variants with complex diseases and traits may lead to the discovery and validation of novel therapeutic targets. Current approaches predict high-confidence LoF variants without identifying the specific genes or the number of copies they affect. Moreover, there is a lack of methods for detecting knockout genes caused by compound heterozygous (CH) LoF variants. RESULTS:We have developed the Loss-of-Function ToolKit (LoFTK), which allows efficient and automated prediction of LoF variants from genotyped, imputed and sequenced genomes. LoFTK enables the identification of genes that are inactive in one or two copies and provides summary statistics for downstream analyses. LoFTK can identify CH LoF variants, which result in LoF genes with two copies lost. Using data from parents and offspring we show that 96% of CH LoF genes predicted by LoFTK in the offspring have the respective alleles donated by each parent. CONCLUSIONS:LoFTK is a command-line based tool that provides a reliable computational workflow for predicting LoF variants from genotyped and sequenced genomes, identifying genes that are inactive in 1 or 2 copies. LoFTK is an open software and is freely available to non-commercial users at https://github.com/CirculatoryHealth/LoFTK .

INTRODUCTION/UNASSIGNED:Genome-wide association studies have discovered common polymorphisms in regions associated with schizophrenia. No genome-wide analyses have been performed in Saudi schizophrenia subjects. METHODS/UNASSIGNED:Genome-wide genotyping data from 136 Saudi schizophrenia cases and 97 Saudi controls in addition to 4,625 American were examined for copy number variants (CNVs). A hidden Markov model approach was used to call CNVs. RESULTS/UNASSIGNED: = 0.04). The analyses focused on extremely large >250 kilobases CNVs or homozygous deletions of any size. One extremely large deletion was noted in a single case (16.5 megabases on chromosome 10). Two cases had an 814 kb duplication of chromosome 7 spanning a cluster of genes, including circadian-related loci, and two other cases had 277 kb deletions of chromosome 9 encompassing an olfactory receptors gene family. CNVs were also seen in loci previously associated with schizophrenia, namely a 16p11 proximal duplication and two 22q11.2 deletions. DISCUSSION/UNASSIGNED:Runs of homozygosity (ROHs) were analyzed across the genome to investigate correlation with schizophrenia risk. While rates and sizes of these ROHs were similar in cases and controls, we identified 10 regions where multiple cases had ROHs and controls did not.

BACKGROUND:Epilepsy, a serious chronic neurological condition effecting up to 100 million people globally, has clear genetic underpinnings including common and rare variants. In Saudi Arabia, the prevalence of epilepsy is high and caused mainly by perinatal and genetic factors. No whole-exome sequencing (WES) studies have been performed to date in Saudi Arabian epilepsy cohorts. This offers a unique opportunity for the discovery of rare genetic variants impacting this disease as there is a high rate of consanguinity among large tribal pedigrees. RESULTS:We performed WES on 144 individuals diagnosed with epilepsy, to interrogate known epilepsy-related genes for known and functional novel variants. We also used an American College of Medical Genetics (ACMG) guideline-based variant prioritization approach in an attempt to discover putative causative variants. We identified 32 potentially causative pathogenic variants across 30 different genes in 44/144 (30%) of these Saudi epilepsy individuals. We also identified 232 variants of unknown significance (VUS) across 101 different genes in 133/144 (92%) subjects. Strong enrichment of variants of likely pathogenicity was observed in previously described epilepsy-associated loci, and a number of putative pathogenic variants in novel loci are also observed. CONCLUSION:Several putative pathogenic variants in known epilepsy-related loci were identified for the first time in our population, in addition to several potential new loci which may be prioritized for further investigation.

BACKGROUND:Large-scale gut microbiome sequencing has revealed key links between microbiome dysfunction and metabolic diseases such as type 2 diabetes (T2D). To date, these efforts have largely focused on Western populations, with few studies assessing T2D microbiota associations in Middle Eastern communities where T2D prevalence is now over 20%. We analyzed the composition of stool 16S rRNA from 461 T2D and 119 non-T2D participants from the Eastern Province of Saudi Arabia. We quantified the abundance of microbial communities to examine any significant differences between subpopulations of samples based on diabetes status and glucose level. RESULTS:In this study we performed the largest microbiome study ever conducted in Saudi Arabia, as well as the first-ever characterization of gut microbiota T2D versus non-T2D in this population. We observed overall positive enrichment within diabetics compared to healthy individuals and amongst diabetic participants; those with high glucose levels exhibited slightly more positive enrichment compared to those at lower risk of fasting hyperglycemia. In particular, the genus Firmicutes was upregulated in diabetic individuals compared to non-diabetic individuals, and T2D was associated with an elevated Firmicutes/Bacteroidetes ratio, consistent with previous findings. CONCLUSION:Based on diabetes status and glucose levels of Saudi participants, relatively stable differences in stool composition were perceived by differential abundance and alpha diversity measures. However, community level differences are evident in the Saudi population between T2D and non-T2D individuals, and diversity patterns appear to vary from well-characterized microbiota from Western cohorts. Comparing overlapping and varying patterns in gut microbiota with other studies is critical to assessing novel treatment options in light of a rapidly growing T2D health epidemic in the region. As a rapidly emerging chronic condition in Saudi Arabia and the Middle East, T2D burdens have grown more quickly and affect larger proportions of the population than any other global region, making a regional reference T2D-microbiome dataset critical to understanding the nuances of disease development on a global scale.