Biology subjects

Kachuri, L.

Publications and source records attributed to Kachuri, L..

8 recordsLinked to original sources

bioRxiv2025

Allele Frequencies at Recessive Disease Genes are Mainly Determined by Pleiotropic Effects in Heterozygotes

The classic theory of mutation-selection balance predicts the equilibrium frequency of genetic variation under negative selection. The model predicts a simple relationship between the total frequency of deleterious variants, mutation rate, and strength of selection, with different functions for recessive and (co-)dominant genes. In this study, we investigate whether genes associated with human recessive disorders fit the predictions of this classic model. By comparing observed frequencies of loss of function variants (LoFs) to those expected under mutation-selection balance we find that, for nearly all recessive genes, the observed frequencies are too low to be explained by purely recessive selection. Analyzing the effects of heterozygous LoFs on quantitative traits from the UK Biobank, we find that recessive disease genes have widespread quantitative effects in heterozygotes. Together, these results suggest that most selection experienced by pathogenic mutations in recessive disease genes may be due to stabilizing selection in heterozygotes. We conclude that very few human genes follow the classic model of recessive mutation-selection balance.

genetics↗

bioRxiv2023

The full spectrum of OCT1 (SLC22A1) mutations bridges transporter biophysics to drug pharmacogenomics

Membrane transporters play a fundamental role in the tissue distribution of endogenous compounds and xenobiotics and are major determinants of efficacy and side effects profiles. Polymorphisms within these drug transporters result in inter-individual variation in drug response, with some patients not responding to the recommended dosage of drug whereas others experience catastrophic side effects. For example, variants within the major hepatic Human organic cation transporter OCT1 (SLC22A1) can change endogenous organic cations and many prescription drug levels. To understand how variants mechanistically impact drug uptake, we systematically study how all known and possible single missense and single amino acid deletion variants impact expression and substrate uptake of OCT1. We find that human variants primarily disrupt function via folding rather than substrate uptake. Our study revealed that the major determinants of folding reside in the first 300 amino acids, including the first 6 transmembrane domains and the extracellular domain (ECD) with a stabilizing and highly conserved stabilizing helical motif making key interactions between the ECD and transmembrane domains. Using the functional data combined with computational approaches, we determine and validate a structure-function model of OCT1s conformational ensemble without experimental structures. Using this model and molecular dynamic simulations of key mutants, we determine biophysical mechanisms for how specific human variants alter transport phenotypes. We identify differences in frequencies of reduced function alleles across populations with East Asians vs European populations having the lowest and highest frequency of reduced function variants, respectively. Mining human population databases reveals that reduced function alleles of OCT1 identified in this study associate significantly with high LDL cholesterol levels. Our general approach broadly applied could transform the landscape of precision medicine by producing a mechanistic basis for understanding the effects of human mutations on disease and drug response.

biophysics↗

bioRxiv2022

Inverted genomic regions between reference genome builds in humans impact imputation accuracy and decrease the power of association testing

Over the last two decades, the human reference genome has undergone multiple updates as we complete a linear representation of our genome. There are two versions of human references currently used in the biomedical literature, GRCh37/hg19 and GRCh38, and conversions between these versions are critical for quality control, imputation, and association analysis. In the present study we show that genomic coordinates for single nucleotide variants (SNVs) in regions inverted between different builds of the reference genome are erroneously converted by the TOPMed imputation server. Depending on the array type, we estimate the inappropriate conversions of variant coordinates would occur in about 2-5 Mb of the genome. Independent of the imputation server, however, in-house conversions of variant coordinates are routine yet impact of mapped variants to these inverted regions and its downstream analytical consequences are underrecognized. We observed that errors for palindromic variants in these inverted regions cannot be detected by standard quality control procedures and destabilize the local haplotype structure, leading to loss of imputation accuracy and power in association analyses. Though only a small proportion of the genome is affected, we show that these regions include important disease susceptibility variants that would be lost due to poor imputation. For example, we show that a known locus associated with prostate cancer on chr10 would have its association P-value drop from 2.86x10-7 to 0.0011 in a case-control analysis of 20,286 Africans and African Americans (10,643 cases and 9,643 controls). We devise a straight-forward heuristic based on the popular tool liftOver that can easily detect and correct these variants in the inverted regions between genome builds to locally improve imputation accuracy.

genomics↗

bioRxiv2021

Gene expression in African Americans and Latinos reveals ancestry-specific patterns of genetic architecture

We analyzed whole genome and RNA sequencing data from 2,733 African American and Hispanic/Latino children to explore ancestry- and heterozygosity-related differences in the genetic architecture of whole blood gene expression. We found that heritability of gene expression significantly increases with greater proportion of African genetic ancestry and decreases with higher levels of Indigenous American ancestry, consistent with a relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of statistically significant ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most of the anc-eQTLs (89%) were driven by population differences in allele frequency, demonstrating the importance of measuring gene expression across multiple populations. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait pairs using models trained in our admixed population than models trained in GTEx. Our study highlights the importance of large and ancestrally diverse genomic studies for enabling new discoveries of complex trait architecture and reducing disparities.

genetics↗

bioRxiv2020

Association Study of Over 200,000 Subjects Detects Novel Rare Variants, Functional Elements, and Polygenic Architecture of Prostate Cancer Susceptibility

The potential association between rare germline genetic variants and prostate cancer (PrCa) susceptibility has been understudied due to challenges with assessing rare variation. Furthermore, although common risk variants for PrCa have shown limited individual effect sizes, their cumulative effect may be of similar magnitude as high penetrance mutations. To identify rare variants associated with PrCa susceptibility, and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we analyzed large population-based cohorts, custom genotyping microarrays, and imputation reference panels in an integrative study of PrCa genetic etiology. In particular, 11,649 men (6,196 PrCa cases, 5,453 controls) of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health, ProHealth Study, and California Mens Health Study were genotyped and meta-analyzed with 196,269 European-ancestry male subjects (7,917 PrCa cases, 188,352 controls) from the UK Biobank. Six novel loci were genome-wide significant in our meta-analysis, including two rare variants (minor allele frequency < 0.01, at 3p21.31 and 8p12). Gene-based rare variant tests implicated a previously discovered PrCa gene (HOXB13) as well as a novel candidate (ILDR1) highly expressed in prostate tissue. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. Furthermore, a polygenic risk score (PRS) of 187 known, largely common PrCa variants was strongly associated with risk in non-Hispanic whites (90th vs. 10th decile OR = 7.66, P = 1.80*10-239). Many of the 187 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a six-fold difference in log-probability of Androgen Receptor binding at the variant rs2680708 (17q22). Our finding of two novel rare variants associated with PrCa should motivate further consideration of the role of low frequency polymorphisms in PrCa, while the considerable effect of PrCa PRS profiles should prompt discussion of their role in clinical practice.

genomics↗

bioRxiv2020

Integration of polygenic risk scores with modifiable risk factors improves risk prediction: results from a pan-cancer analysis

Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude of this improvement varies substantially. We also demonstrate that stratifying on levels of PRS identifies significantly divergent 5-year risk trajectories after accounting for family history and modifiable risk factors. At the population level, the top 20% of the PRS distribution accounts for 4.0% to 30.3% of incident cancer cases, exceeding the impact of many lifestyle-related factors. In summary, this study illustrates the potential for improving cancer risk assessment by integrating genetic risk scores.

genetics↗

bioRxiv2019

Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility

Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: rg=0.098, p=2.3x10-8) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: rg=0.137, p=2.0x10-12). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR)=1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR=1.17, 1.01-1.35) and lung cancer in never smokers (OR=1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.

genetics↗

bioRxiv2019

Pan-Cancer Study Detects Novel Genetic Risk Variants and Shared Genetic Basis in Two Large Cohorts

Deciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. However, no studies have investigated pan-cancer pleiotropy within single, well-defined populations unselected for phenotype. We undertook novel genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (413,870 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detected 21 novel genome-wide significant risk variants. In addition, numerous cancer sites exhibited clear heritability. Investigations of pleiotropy identified 12 cancer pairs exhibiting either positive or negative genetic correlations and 43 pleiotropic loci. We identified 158 pleiotropic variants, many of which were enriched for regulatory elements and influenced cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.

genetics↗