Biology subjects

Patel, B.

Publications and source records attributed to Patel, B..

3 recordsLinked to original sources

bioRxiv2018

Molecular Screening of Familial Hypercholesterolemia in the Icelandic Population

Familial hypercholesterolemia (FH) is a monogenic disease characterized by a lifelong exposure to high LDL-C levels that can lead to early onset coronary heart disease (CHD). The main causes of FH identified to date include loss-of-function mutations in LDLR or APOB, or gain-of-function mutations in PCSK9. Early diagnosis and genetic testing of FH suspects is critical for improved prognosis of affected individuals as lipid lowering treatments are effective in preventing CHD related morbidity and mortality. In the present manuscript, we developed a comprehensive next generation sequencing (NGS) panel which we applied on two different resources of FH in the Icelandic population: 62 subjects from 23 FH families with known or unknown culprit mutations, and a population-based sampling of 315 subjects selected for total cholesterol levels above the 95th percentile cut-point. The application of the NGS panel revealed significant diagnostic yields in identifying pathogenic LDLR mutations in both family and population-based genetic testing.

genetics↗

bioRxiv2018

Comprehensive Genetic Testing for Female and Male Infertility Using Next Generation Sequencing

ObjectiveTo develop a comprehensive genetic test for female and male infertility in support of medical decisions during assisted reproductive technology (ART) protocols.\n\nDesignRetrospective analysis of results from 118 DNA samples with known variants in loci representative of female and male infertility.\n\nInterventions(s)None\n\nMain Outcome Measure(s)Next-Generation Sequencing (NGS) of 87 genes including promoters, 5 and 3 untranslated regions, exons and selected introns. In addition, sex chromosome aneuploidies and Y chromosome microdeletions are analyzed concomitantly using the same panel.\n\nResultsAnalytical accuracy was >99%, with >98% sensitivity for Single Nucleotide Variants (SNVs) and >91% sensitivity for insertions/deletions (indels). Clinical sensitivity was assessed with samples containing variants representative of male and female infertility, and it was 100% for SNVs/indels, CFTR IVS8-5T variants, sex chromosome aneuploidies and Copy Number Variants (CNVs), and >93% for Y chromosome microdeletions. Cost analysis comparing the NGS assay with standard, multiple analysis approach, shows potential savings of $2723 per case. Conclusion: A single, comprehensive, NGS panel can simplify the ordering process for healthcare providers, reduce turnaround time, and lower the overall cost of testing for genetic assessment of infertility in females and males, while maintaining accuracy.

genomics↗

bioRxiv2017

Do Candidate Genes Affect the Brain’s White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI Scans

AbstractSusceptibility genes for psychiatric and neurological disorders - including APOE, BDNF, CLU,CNTNAP2, COMT, DISC1, DTNBP1, ErbB4, HFE, NRG1, NTKR3, and ZNF804A - have been reported to affect white matter (WM) microstructure in the healthy human brain, as assessed through diffusion tensor imaging (DTI). However, effects of single nucleotide polymorphisms (SNPs) in these genes explain only a small fraction of the overall variance and are challenging to detect reliably in single cohort studies. To date, few studies have evaluated the reproducibility of these results. As part of the ENIGMA-DTI consortium, we pooled regional fractional anisotropy (FA) measures for 6,165 subjects (CEU ancestry N=4,458) from 11 cohorts worldwide to evaluate effects of 15 candidate SNPs by examining their associations with WM microstructure. Additive association tests were conducted for each SNP. We used several meta-analytic and mega-analytic designs, and we evaluated regions of interest at multiple granularity levels. The ENIGMA-DTI protocol was able to detect single-cohort findings as originally reported. Even so, in this very large sample, no significant associations remained after multiple-testing correction for the 15 SNPs investigated. Suggestive associations (1.3x10-4 < p < 0.05, uncorrected) were found for BDNF, COMT, and ZNF804A in specific tracts. Meta-and mega-analyses revealed similar findings. Regardless of the approach, the previously reported candidate SNPs did not show significant associations with WM microstructure in this largest genetic study of DTI to date; the negative findings are likely not due to insufficient power. Genome-wide studies, involving large-scale meta-analyses, may help to discover SNPs robustly influencing WM microstructure.

neuroscience↗