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Summary Human pluripotent stem cell-derived kidney organoids recapitulate developmental processes and tissue architecture, but intrinsic limitations, such as lack of vasculature and functionality, have greatly hampered their application. Here we establish a versatile protocol for generating vascularized three-dimensional (3D) kidney organoids. We employ dynamic modulation of WNT signaling to control the relative proportion of proximal versus distal nephron segments, producing a correlative level of vascular endothelial growth factor A (VEGFA) to define a resident vascular network. Single-cell RNA sequencing identifies a subset of nephron progenitor cells as a potential source of renal vasculature. These kidney organoids undergo further structural and functional maturation upon implantation. Using this kidney organoid platform, we establish an in vitro model of autosomal recessive polycystic kidney disease (ARPKD), the cystic phenotype of which can be effectively prevented by gene correction or drug treatment. Our studies provide new avenues for studying human kidney development, modeling disease pathogenesis, and performing patient-specific drug validation.

We report on three new patients with spondyloocular syndrome (SOS) in a consanguineous Pakistani family. All three patients present progressive generalized osteoporosis, short stature, recurrent fractures, hearing loss and visual impairments. WES revealed a novel homozygous frameshift variant in exon 11 of XYLT2 (NG 012175.1, NP_071450.2) resulting in loss of evolutionary conserved amino acid sequences (840 – 865/865) at C-terminus p.R840fs∗115. Sanger Sequencing confirmed the presence of the novel homozygous mutation in all three patients while the parents were heterozygous carriers of the mutation, in accordance with an autosomal recessive inheritance pattern. Only nine variants worldwide have previously been reported in XYLT2 in patients with SOS phenotype. These three patients with novel homozygous variant extend the genotypic and phenotypic spectrum of SOS. NRF (Natl Research Foundation, S’pore) Published version

Importance Large-scale genome-wide association studies in the European population have identified 90 risk variants associated with Parkinson disease (PD); however, there are limited studies in the largest population worldwide (ie, Asian). Objectives To identify novel genome-wide significant loci for PD in Asian individuals and to compare genetic risk between Asian and European cohorts. Design Setting, and Participants Genome-wide association data generated from PD cases and controls in an Asian population (ie, Singapore/Malaysia, Hong Kong, Taiwan, mainland China, and South Korea) were collected from January 1, 2016, to December 31, 2018, as part of an ongoing study. Results were combined with inverse variance meta-analysis, and replication of top loci in European and Japanese samples was performed. Discovery samples of 31 575 individuals passing quality control of 35 994 recruited were used, with a greater than 90% participation rate. A replication cohort of 1 926 361 European-ancestry and 3509 Japanese samples was analyzed. Parkinson disease was diagnosed using UK Parkinson’s Disease Society Brain Bank Criteria. Main Outcomes and Measures Genotypes of common variants, association with disease status, and polygenic risk scores. Results Of 31 575 samples identified, 6724 PD cases (mean [SD] age, 64.3 [10] years; age at onset, 58.8 [10.6] years; 3472 [53.2%] men) and 24 851 controls (age, 59.4 [11.4] years; 11 030 [45.0%] men) were analyzed in the discovery study. Eleven genome-wide significant loci were identified; 2 of these loci were novel (SV2CandWBSCR17) and 9 were previously found in Europeans. Replication in European-ancestry and Japanese samples showed robust association forSV2C(rs246814; odds ratio, 1.16; 95% CI, 1.11-1.21;P = 1.17 × 10−10in meta-analysis of discovery and replication samples) but showed potential genetic heterogeneity atWBSCR17(rs9638616;I2=67.1%;P = 3.40 × 10−3for hetereogeneity). Polygenic risk score models including variants at these 11 loci were associated with a significant improvement in area under the curve over the model based on 78 European loci alone (63.1% vs 60.2%;P = 6.81 × 10−12). Conclusions and Relevance This study identified 2 apparently novel gene loci and found 9 previously identified European loci to be associated with PD in this large, meta–genome-wide association study in a worldwide population of Asian individuals and reports similarities and differences in genetic risk factors between Asian and European individuals in the risk for PD. These findings may lead to improved stratification of Asian patients and controls based on polygenic risk scores. Our findings have potential academic and clinical importance for risk stratification and precision medicine in Asia.

A recent meta-analysis of Parkinson's disease (PD) genome-wide association studies has identified 17 novel risk loci in the European population. We aim to assess if these reported novel risk loci are similarly implicated in PD risk within the East Asian population by analyzing the reported risk single nucleotide polymorphism or proxy single nucleotide polymorphism in 14,006 East Asian samples (779 patients and 13,227 controls). We found that 9 of the 17 reported novel PD risk loci showed very similar effects in Europeans and East Asians (I2 = 0 to 10.7%), of which 2 loci ITPKB and ZNF184 were significantly associated with PD in our samples. Two of the reported risk loci, ANK2/CAMK2D and CTSB, were non-polymorphic in East Asians and therefore not implicated in PD risk in the East Asian population. Given the small effect sizes of these risk loci, further validation is needed in additional Asian samples. NRF (Natl Research Foundation, S’pore) ASTAR (Agency for Sci., Tech. and Research, S’pore) NMRC (Natl Medical Research Council, S’pore) Accepted version

Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions or deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ∼24,800 years ago and experienced significant admixture with East Asians ∼1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, 14 of which harbored robust associations with complex traits and diseases. Finally, we show that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Accepted version We acknowledge H.M. Kang, S. Das, A. Tan, F. Zhang, J. Terhorst, P.-R. Loh, and G. Hellenthal for helpful discussions and support from all participants and clinical research coordinators of the contributing cohorts and studies: the TTSH Healthy Control Workgroup, the SEED cohort, the Asian Sudden Cardiac Death in Heart Failure Study, the Singapore Heart Failure Outcomes and Phenotypes (SHOP) cohort, the Asian neTwork for Translational Research and Cardiovascular Trials (ATTRaCT), the Parkinson’s Disease Study, the Peranakan Genome Study, the Platinum Asian Genomes Project, the Bariatric Surgery Study, the National Heart Centre Singapore Biobank and SingHEART cohorts, and the GUSTO and S-PRESTO study groups. This study was supported by Singapore’s A*STAR (core funding and IAF-PP H17/01/a0/007), BMRC (SPF2014/001, SPF2013/002, SPF2014/003, SPF2014/004, and SPF2014/005), NMRC (CIRG/1371/2013, CIRG/1417/2015, CIRG/1488/ 2018, CSA-SI/0012/2017, CG/017/2013, CG/M006/2017_NHCS, TCR/013- NNI/2014, STaR/0011/2012, STaR2013/001, STaR/014/2013, STaR/0026/ 2015, TCR/006-NUHS/2013, TCR/012-NUHS/2014, TCR/004-NUS/2008, TCR/012-NUHS/2014, and center grants 2010-13 and 2013-2017), NRF (NRFF2016-03), National University of Singapore, SingHealth and DukeNUS, and Alexandra Health small innovative grant SIGII/15203 and funding from Huazhong University of Science and Technology, the Tanoto Foundation, the Lee Foundation, the Boston Scientific Investigator Sponsored Research Program and Bayer, the NSF (DEB-1753489), and the Alfred P. Sloan Foundation. The computation was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg).