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Andrew D Paterson

Publications and source records attributed to Andrew D Paterson.

2 recordsLinked to original sources

Assessing Hardy-Weinberg equilibrium in T2T-aligned 1000 genomes project.

Quality control of markers in genome-wide association studies often includes testing for Hardy-Weinberg equilibrium (HWE). However, this is usually implemented in a homogeneous population without stratifying by sex. Previous work indicates sex-based selection at numerous autosomal loci in cohorts with active recruitment. Sex chromosome sequences can also interfere with autosomal SNPs. These motivate a re-examination of HWE in sex-aware analyses. Using the telomere-to-telomere (T2Tv2)-aligned high-coverage whole genome sequencing data from 2,490 individuals in the 1000 Genomes Project, we examined genome-wide sex-specific deviations from HWE across five super-populations. Our analyses were restricted to bi-allelic SNPs with non-missing genotypes and minor allele frequency (MAF) &#x2265;5% in both sexes of the five super-populations. We applied an allele-based framework to quantify both the magnitude and direction of Hardy-Weinberg disequilibrium (HWD), followed by a second-order omnibus meta-analysis that combined HWD results across populations and sexes. At a genome-wide significance threshold of p&#x2009;<&#x2009;5e-8, 0.9% of autosomal SNPs exhibited significant deviations from HWE. The majority of these deviations were associated with genomic features indicative of poor sequence quality. Restricting the analysis to reliable genomic regions substantially reduced the number of signals, yielding 255 autosomal SNPs and one non-pseudoautosomal chromosome X SNP. Among these, 140 autosomal SNPs displayed significant heterogeneity across populations but not across sexes. Notably, eight SNPs within a 15-bp region on chromosome 14q31.3 showed excess heterozygosity in both sexes of the African super-population (AFR). Finally, we developed a multivariate predictor of HWD based on sequence features, providing a practical tool that can be integrated into existing quality control pipelines for whole genome sequencing studies.

Journal Article

Genetic Risk Factors for Kidney Function in Individuals with Type 1 Diabetes.

KEY POINTS: Previous research has identified polygenic risk scores that are associated with low eGFR and albuminuria in the general population. We observed that these eGFR and albuminuria polygenic risk scores were associated with eGFR and albuminuria, respectively, in type 1 diabetes. Associations were independent of glycemic control and suggest shared genetic kidney risk factors between type 1 diabetes and the general population. BACKGROUND: Genetic risk factors underlying kidney disease in type 1 diabetes (T1D) remain poorly understood. We examined whether previously established polygenic risk scores (PRS) for eGFR and albuminuria are associated with these measures in adults with T1D in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications study. METHODS: We applied eGFR and albuminuria PRS derived in general population cohorts to 1304 DCCT/Epidemiology of Diabetes Interventions and Complications participants with genome-wide genotyping. We tested PRS associations with eGFR and urine albumin excretion rate (AER) as well as incident eGFR <60 ml/min per 1.73 m 2 , AER &#x2265;30 mg/24 h, and AER &#x2265;300 mg/24 h. For consistency, PRS values were linearly transformed so higher scores corresponded to higher eGFR and AER. We also examined associations of kidney outcomes with rs55703767 in COL4A3 , which has previously been associated with CKD in T1D. RESULTS: At DCCT baseline, participants had a mean age of 27 years; 53% were male. 49% of participants were randomized to intensive versus conventional glucose-lowering therapy. Participants were followed for median of (first-third quartiles) 35 (33-37) years. The eGFR PRS was significantly associated with continuous eGFR (per one SD higher PRS 2.72 ml/min per 1.73 m 2 higher [95% confidence interval (CI), 2.05 to 3.40]) and incident eGFR <60 ml/min per 1.73 m 2 (hazard ratio [HR]=0.82 [95% CI, 0.73 to 0.92]), but not consistently with albuminuria. There was no association with quantitative AER (2.42 mg/24 h [95% CI, -1.86 to 6.89]) or sustained AER &#x2265;30 mg/24 h (HR=1.03; [95% CI, 0.94 to 1.14]). The albuminuria PRS was significantly associated with incident AER &#x2265;30 mg/24 h (HR=1.12 [95% CI, 1.02 to 1.22]) but not continuous eGFR (0.49 ml/min per 1.73 m 2 higher [95% CI, -0.23 to 1.21]) or incident eGFR <60 ml/min per 1.73 m 2 (HR=0.96 [95% CI, 0.85 to 1.08]). Associations were similar in analyses stratified by DCCT treatment group assignment. rs55703767 was associated with lower incident macroalbuminuria in the overall cohort (HR=0.77 per minor allele [95% CI, 0.59 to 0.99]), and upon stratification by DCCT treatment group assignment, only within the conventional and not intensive glucose-lowering therapy group. CONCLUSIONS: PRS associated with eGFR and albuminuria in the general population were associated with corresponding measures in adults with T1D. The results suggest shared genetic risk factors for kidney disease between T1D and the general population but different genetic risk factors for albuminuria and eGFR in T1D. CLINICAL TRIALS REGISTRATION NUMBERS: NCT00360893 , NCT00360815 .

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