Biology subjects

Patel, K. A.

Publications and source records attributed to Patel, K. A..

8 recordsLinked to original sources

bioRxiv2026

Federated cross-biobank conditional analysis identifies LDL-C lowering effects of DNAJC13 haploinsufficiency and LDLR regulation

Whole genome sequencing in diverse population-scale biobanks offers new insights into the genetic architecture of complex traits from rare and non-coding variants. However, rare single variant and aggregate associations are often confounded by linkage disequilibrium and haplotype structure, resulting in large numbers of false-positive associations. Previous methods that rely on reference panels or linkage disequilibrium-matrices to determine conditional independence in meta-analyses do not scale to very rare variants, which may be observed in only one biobank and can exhibit long-range haplotypes. Here, we implement a federated approach to perform iterative conditional meta-analysis on individual-level genotype and phenotype data across biobanks while adhering to data sharing policies. We applied our methodology to a meta-analysis of LDL-C in 614,375 individuals from UK Biobank and All of Us, encompassing six genetic ancestry groups. After conditioning, only 4.3% of significantly associated rare single variants and 6.9% of aggregates remained statistically independent. The proportion of significant aggregates that remained independent after conditioning was higher for coding-based tests than non-coding. We further validate that our approach effectively suppresses false-positive associations using simulations centred on the LDLR locus. We identify allelic series of variants associated with reduced LDL-C, including loss-of-function variants in DNAJC13 and variants in the 3-prime untranslated region of LDLR. Our results highlight that federated conditioning can distinguish independent rare variant signals from linkage and haplotype structure artifacts in multi-ancestry meta-analyses across separate biobanks.

genetics↗

bioRxiv2025

Uncovering genetic architecture of the heart via genetic association studies of unsupervised deep learning derived endophenotypes

Recent genome-wide association studies (GWAS) have effectively linked genetic variants to quantitative traits derived from time-series cardiac magnetic resonance imaging, revealing insights into cardiac morphology and function. Deep learning approach generally requires extensive supervised training on manually annotated data. In this study, we developed a novel framework using a 3D U-architecture autoencoder (cineMAE) to learn deep image phenotypes from cardiac magnetic resonance (CMR) imaging for genetic discovery, focusing on long-axis two-chamber and four-chamber views. We trained a masked autoencoder to develop Unsupervised Derived Image Phenotypes for heart (Heart-UDIPs). These representations were found to be informative to indicate various heart-specific phenotypes (e.g., left ventricular hypertrophy) and diseases (e.g., hypertrophic cardiomyopathy). GWAS on Heart UDIP identified 323 lead SNP and 628 SNP-prioritized genes, which exceeded previous methods. The genes identified by method described herein, exhibited significant associations with cardiac function and showed substantial enrichment in pathways related to cardiac disorders. These results underscore the utility of our Heart-UDIP approach in enhancing the discovery potential for genetic associations, without the need for clinically defined phenotypes or manual annotations.

bioinformatics↗

bioRxiv2025

Exogenous Delivery of Sphingomyelinase Mediates Mesenchymal Stromal Cell-Extracellular Vesicle Biogenesis, Alters Cargo Sorting, and Therapeutic Potency in vitro

Mesenchymal stromal cells (MSCs) exert regenerative and immunomodulatory effects largely through secreted paracrine factors and extracellular vesicles (EVs), which transfer proteins, lipids, and nucleic acids to recipient cells. Lipid composition critically influences EV stability, uptake, and bioactivity. Sphingomyelinase (SMase), an enzyme that hydrolyzes sphingomyelin into ceramide, regulates EV biogenesis by inducing membrane curvature and initiating inward membrane budding. Here, MSCs were treated with SMase, and EVs were isolated and characterized by nanoparticle tracking analysis, miRNA sequencing, lipidomics, and proteomics. SMase treatment increased EV yield and altered lipid, protein, and miRNA cargo linked to TNF- signaling, wound healing, and angiogenesis. Functionally, SMase-EVs suppressed TNF- in macrophages, showed trending increased HUVEC tubular formation, and altered T-cell populations following local delivery in a critical murine oral wound defect model. These findings highlight how enzymatic lipid remodeling modifies MSC-EVs, enhancing their therapeutic potential and informing strategies for optimized EV-based therapies and scalable production.

bioengineering↗

bioRxiv2025

Mitochondrial heterogeneity disrupts osteoclast differentiation and bone resorption by impairing respiratory complex I

Mitochondrial heteroplasmy, the co-existence of different mitochondrial genomes within a cell, is linked to aging and disease. Patients with heteroplasmy due to mitochondrial mutations experience multiple organ complications, particularly poor bone health and bone structure defects. However, the mechanisms involved are generally unknown, due largely to the difficulty of manipulating mtDNA in vivo. To overcome this, we leveraged a heteroplasmic mouse model and discovered that mitochondrial heteroplasmy affects a fundamental developmental process. Specifically, the differentiation of osteoclasts, which resorb bone tissue and maintain bone homeostasis. Mechanistically, there was a reduced localization of specifically respiratory complex I subunits in mitochondria in heteroplasmic mice, disrupting ATP production and osteoclast differentiation. In addition, autophagic flux is exhausted, and the autophagy inducer spermidine restores mitochondrial health and rescues osteoclast activity, both in mice and in cells from patients with primary mitochondrial disease. Together, we identify the mechanisms by which mitochondrial heteroplasmy impacts osteoclastogenesis and discover spermidine as a modulator of this process, which presents a potential treatment for human heteroplasmic conditions such as mitochondrial diseases, which are largely untreatable. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/651799v4_ufig1.gif" ALT="Figure 1"> View larger version (94K): org.highwire.dtl.DTLVardef@131d3f6org.highwire.dtl.DTLVardef@52bf2aorg.highwire.dtl.DTLVardef@848bb3org.highwire.dtl.DTLVardef@1efa572_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2023

Whole genome sequencing analysis identifies rare, large-effect non-coding variants and regions associated with circulating protein levels

The role of non-coding rare variation in common phenotypes is largely unknown, due to a lack of whole-genome sequence data, and the difficulty of categorising non-coding variants into biologically meaningful regulatory units. To begin addressing these challenges, we performed a cis association analysis using whole-genome sequence data, consisting of 391 million variants and 1,450 circulating protein levels in [~]20,000 UK Biobank participants. We identified 777 independent rare non-coding single variants associated with circulating protein levels (P<1x10-9), after conditioning on protein-coding and common associated variants. Rare non-coding aggregate testing identified 108 conditionally independent regulatory regions. Unlike protein-coding variation, rare non-coding genetic variation was almost as likely to increase as decrease protein levels. The regions we identified overlapped predicted tissue-specific enhancers more than promoters, suggesting they represent tissue-specific regulatory regions. Our results have important implications for the identification, and role, of rare non-coding variation associated with common human phenotypes.

genetics↗

bioRxiv2019

Women with isolated fasting hyperglycemia in pregnancy are at a higher genetic risk for type 2 diabetes

BackgroundUsing genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. MethodsCases were divided into three subgroups: (i) FPG [≥]5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load [≥]10 mmol/L only, n=154 (iii) 2-hour glucose [≥]8.5 mmol/L only, n=73); and (iv) both FPG [≥]5.1 mmol/L and either of a 1-hour glucose [≥]10 mmol/L or 2-hour glucose [≥]8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. ResultsIn HAPO and DIP, the mean FPG GS in women with a FPG [≥]5.1 mmol/L, either on its own or with 1-hour glucose [≥]10 mmol/L or 2-hour glucose [≥]8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). ConclusionsThe different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

genetics↗

bioRxiv2019

SavvyCNV: genome-wide CNV calling from off-target reads

Identifying copy number variants (CNVS) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data to call CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions - SavvyCNV exploits this free data.\n\nWe benchmarked SavvyCNV using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming five state-of-the-art CNV callers at calling CNVs genome-wide using off-target or on-target reads from targeted panel and exome sequencing. Furthermore SavvyCNV was able to call previously undetected clinically-relevant CNVs from targeted panel data highlighting the utility of this tool within the diagnostic setting. SavvyCNV is freely available.

bioinformatics↗

bioRxiv2017

Heterozygous RFX6 protein truncating variants cause Maturity-Onset Diabetes of the Young (MODY) with reduced penetrance

Finding new genetic causes of monogenic diabetes can help to understand development and function of the human pancreas. We aimed to find novel protein-truncating variants causing Maturity-Onset Diabetes of the Young (MODY), a subtype of monogenic diabetes. We used a combination of next-generation sequencing of MODY cases with unknown aetiology along with comparisons to the ExAC database to identify new MODY genes. In the discovery cohort of 36 European patients, we identified two probands with novel RFX6 heterozygous nonsense variants. RFX6 protein truncating variants were enriched in the MODY discovery cohort compared to the European control population within ExAC (odds ratio, OR=131, P=lxl0-4). We found similar results in non-Finnish European (n=348, OR=43, P=5xl0-5) and Finnish (n=80, OR=22, P=1xl0-6) replication cohorts. The overall meta-analysis OR was 34 (P=lxl0-16). RFX6 heterozygotes had reduced penetrance of diabetes compared to common HNF1A and HNF4A-MODY mutations (27%, 70% and 55% at 25 years of age, respectively). The hyperglycaemia resulted from beta-cell dysfunction and was associated with lower fasting and stimulated gastric inhibitory polypeptide (GIP) levels. Our study demonstrates that heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance.

genetics↗