Target specific serologic analysis of COVID-19 convalescent plasma.

This study compared the performance of four serology assays for Coronavirus Disease 2019 (COVID-19) and investigated whether COVID-19 disease history correlates with assay performance. Samples were tested at Northshore using the Elecsys Anti-SARS-CoV-2 (Roche Diagnostics), Access SARS-CoV-2 IgG anti-RBD (Beckman Coulter), and LIAISON SARS-CoV-2 S1/S2 IgG (DiaSorin) as well as at Genalyte using Maverick Multi-Antigen Serology Panel. The study included one hundred clinical samples collected before December 2019 and ninety-seven samples collected from convalescent plasma donors originally diagnosed with COVID-19 by PCR. COVID-19 disease history was self-reported by the plasma donors. There was no difference in specificity between the assays tested. Clinical sensitivity of these four tests was 98% (Genalyte), 96% (Roche), 92% (DiaSorin), and 87% (Beckman). The only statistically significant differences in clinical sensitivity was between the Beckman assay and both Genalyte and Roche assays. Convalescent plasma donor characteristics and disease symptoms did not correlate with false negative results from the Beckman and DiaSorin assays. All four tests showed high specificity (100%) and varying sensitivities (89-98%). No correlations between disease history and serology results were observed. The Genalyte Multiplex assay showed as good or better sensitivity to three other previously validated assays with FDA Emergency Use Authorizations.

Utilization of genetic data can improve the prediction of type 2 diabetes incidence in a Swedish cohort.

The aim of this study was to measure the impact of genetic data in improving the prediction of type 2 diabetes (T2D) in the Malmö Diet and Cancer Study cohort. The current study was performed in 3,426 Swedish individuals and utilizes of a set of genetic and environmental risk data. We first validated our environmental risk model by comparing it to both the Finnish Diabetes Risk Score and the T2D risk model derived from the Framingham Offspring Study. The area under the curve (AUC) for our environmental model was 0.72 [95% CI, 0.69-0.74], which was significantly better than both the Finnish (0.64 [95% CI, 0.61-0.66], p-value < 1 x 10-4) and Framingham (0.69 [95% CI, 0.66-0.71], p-value = 0.0017) risk scores. We then verified that the genetic data has a statistically significant positive correlation with incidence of T2D in the studied population. We also verified that adding genetic data slightly but statistically increased the AUC of a model based only on environmental risk factors (RFs, AUC shift +1.0% from 0.72 to 0.73, p-value = 0.042). To study the dependence of the results on the environmental RFs, we divided the population into two equally sized risk groups based only on their environmental risk and repeated the same analysis within each subpopulation. While there is a statistically significant positive correlation between the genetic data and incidence of T2D in both environmental risk categories, the positive shift in the AUC remains statistically significant only in the category with the lower environmental risk. These results demonstrate that genetic data can be used to increase the accuracy of T2D prediction. Also, the data suggests that genetic data is more valuable in improving T2D prediction in populations with lower environmental risk. This suggests that the impact of genetic data depends on the environmental risk of the studied population and thus genetic association studies should be performed in light of the underlying environmental risk of the population.

Genome-wide linkage analysis of a Parkinsonian-pyramidal syndrome pedigree by 500 K SNP arrays.

Robust SNP genotyping technologies and data analysis programs have encouraged researchers in recent years to use SNPs for linkage studies. Platforms used to date have been 10 K chip arrays, but the possible value of interrogating SNPs at higher densities has been considered. Here, we present a genome-wide linkage analysis by means of a 500 K SNP platform. The analysis was done on a large pedigree affected with Parkinsonian-pyramidal syndrome (PPS), and the results showed linkage to chromosome 22. Sequencing of candidate genes revealed a disease-associated homozygous variation (R378G) in FBXO7. FBXO7 codes for a member of the F-box family of proteins, all of which may have a role in the ubiquitin-proteosome protein-degradation pathway. This pathway has been implicated in various neurodegenerative diseases, and identification of FBXO7 as the causative gene of PPS is expected to shed new light on its role. The performance of the array was assessed and systematic analysis of effects of SNP density reduction was performed with the real experimental data. Our results suggest that linkage in our pedigree may have been missed had we used chips containing less than 100,000 SNPs across the genome.

High-resolution quantitative trait locus analysis reveals multiple diabetes susceptibility loci mapped to intervals<800 kb in the species-conserved Niddm1i of the GK rat.

Niddm1i, a 16-Mb locus within the major diabetes QTL in the diabetic GK rat, causes impaired glucose tolerance in the congenic NIDDM1I strain. Niddm1i is homologous to both human and mouse regions linked with type 2 diabetes susceptibility. We employed multiple QTL analyses of congenic F2 progeny selected for one recombination event within Niddm1i combined with characterization of subcongenic strains. Fine mapping located one hyperglycemia locus within 700 kb (Niddm1i4, P=5x10(-6)). Two adjacent loci were also detected, and the GK allele at Niddm1i2 (500 kb) showed a glucose-raising effect, whereas it had a glucose-lowering effect at Niddm1i3 (400 kb). Most proximally, Niddm1i1 (800 kb) affecting body weight was identified. Experimental data from subcongenics supported the four loci. Sorcs1, one of the two known diabetes susceptibility genes in the region, resides within Niddm1i3, while Tcf7l2 maps outside all four loci. Multiple-marker QTL analysis incorporating the effect of cosegregating QTL as cofactors together with genetically selected progeny can remarkably enhance resolution of QTL. The data demonstrate that the species-conserved Niddm1i is a composite of at least four QTL affecting type 2 diabetes susceptibility and that two adjacent QTL (Niddm1i2GK and Niddm1i3GK) act in opposite directions.

Multiplexed variation scanning for 1,000 amplicons in hundreds of patients using mismatch repair detection (MRD) on tag arrays.

Identification of the genetic basis of common disease may require comprehensive sequence analysis of coding regions and regulatory elements in patients and controls to find genetic effects caused by rare or heterogeneous mutations. In this study, we demonstrate how mismatch repair detection on tag arrays can be applied in a case-control study. Mismatch repair detection allows >1,000 amplicons to be screened for variations in a single laboratory reaction. Variation scanning in 939 amplicons, mostly in coding regions within a linkage peak, was done for 372 patients and 404 controls. In total, >180 Mb of DNA was scanned. Several variants more prevalent in patients than in controls were identified. This study demonstrates an approach to the discovery of susceptibility genes for common disease: large-scale direct sequence comparison between patients and controls. We believe this approach can be scaled up to allow sequence comparison in the whole-genome coding regions among large sets of cases and controls at a reasonable cost in the near future.

Age-dependent regulation of lipogenesis in human and rat adipocytes.

The regulation of adipocyte metabolism is of importance for adipose tissue growth and therefore also for the development of obesity. This study was designed to investigate the regulation of basal and insulin-induced lipogenesis, glucose transport, and glucose transporter protein expression in human and rat adipocytes from different age groups. The study included 21 infants, 21 children, nine adults, and 80 male weaned and 20 male adult Fischer rats. The lipogenesis experiments were performed under conditions at which glucose transport is rate limiting. Basal lipogenesis was approximately three times higher in infants and children than in adults, whereas insulin-induced lipogenesis was two times higher in infants than in children and adults. In rats, basal lipogenesis, insulin-induced lipogenesis, and insulin sensitivity were two times higher in weaned than in adult animals. Moreover, basal and insulin-induced glucose transport were two times higher in weaned than in adult rats. No differences were detected in GLUT1 or GLUT4 content between any of the age groups in human or in rat adipocytes. In conclusion, basal and insulin-stimulated lipogenesis are increased in adipocytes early in life. This may promote adipose tissue growth in early age. The data indicate that age-dependent variation in basal and insulin-stimulated lipogenesis is differently regulated.

SNP discovery in pooled samples with mismatch repair detection.

A targeted discovery effort is required to identify low frequency single nucleotide polymorphisms (SNPs) in human coding and regulatory regions. We here describe combining mismatch repair detection (MRD) with dideoxy terminator sequencing to detect SNPs in pooled DNA samples. MRD enriches for variant alleles in the pooled sample, and sequencing determines the nature of the variants. By using a genomic DNA pool as a template, approximately 100 fragments were amplified and subsequently combined and subjected en masse to the MRD procedure. The variant-enriched pool from this one MRD reaction is enriched for the population variants of all the tested fragments. Each fragment was amplified from the variant-enriched pool and sequenced, allowing the discovery of alleles with frequencies as low as 1% in the initial population. Our results support that MRD-based SNP discovery can be used for large-scale discovery of SNPs at low frequencies in a population.

Multiplexed genotyping with sequence-tagged molecular inversion probes.

We report on the development of molecular inversion probe (MIP) genotyping, an efficient technology for large-scale single nucleotide polymorphism (SNP) analysis. This technique uses MIPs to produce inverted sequences, which undergo a unimolecular rearrangement and are then amplified by PCR using common primers and analyzed using universal sequence tag DNA microarrays, resulting in highly specific genotyping. With this technology, multiplex analysis of more than 1,000 probes in a single tube can be done using standard laboratory equipment. Genotypes are generated with a high call rate (95%) and high accuracy (>99%) as determined by independent sequencing.

Pyrosequencing: an accurate detection platform for single nucleotide polymorphisms.

Pyrosequencing, a non-electrophoretic method for DNA sequencing, is emerging as a popular platform for analysis of single nucleotide polymorphisms (SNPs). This technology has the advantage of accuracy, ease-of-use, and high flexibility for different applications. Here, we review the methodology and the use of this technique for SNP genotyping, SNP discovery, haplotyping, and allelic frequency studies. In addition, we describe new schemes for template preparation and multiplexing as an effort for cost reduction in large-scale studies.