Advancing drug discovery using the power of the human genome

Human genetics plays an increasingly important role in drug development and population health. Here we review the history of human genetics in the context of accelerating the discovery of therapies, present examples of how human genetics evidence supports successful drug targets, and discuss how polygenic risk scores could be beneficial in various clinical settings. We highlight the value of direct-to-consumer platforms in the era of fast-paced big data biotechnology, and how diverse genetic and health data can benefit society. © 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Immunoglobulin class-switched B cells form an active immune axis between CNS and periphery in multiple sclerosis

In multiple sclerosis (MS), lymphocyte--in particular B cell--transit between the central nervous system (CNS) and periphery may contribute to the maintenance of active disease. Clonally related B cells exist in the cerebrospinal fluid (CSF) and peripheral blood (PB) of MS patients; however, it remains unclear which subpopulations of the highly diverse peripheral B cell compartment share antigen specificity with intrathecal B cell repertoires and whether their antigen stimulation occurs on both sides of the blood-brain barrier. To address these questions, we combined flow cytometric sorting of PB B cell subsets with deep immune repertoire sequencing of CSF and PB B cells. Immunoglobulin (IgM and IgG) heavy chain variable (VH) region repertoires of five PB B cell subsets from MS patients were compared with their CSF Ig-VH transcriptomes. In six of eight patients, we identified peripheral CD27(+)IgD(-) memory B cells, CD27(hi)CD38(hi) plasma cells/plasmablasts, or CD27(-)IgD(-) B cells that had an immune connection to the CNS compartment. Pinpointing Ig class-switched B cells as key component of the immune axis thought to contribute to ongoing MS disease activity strengthens the rationale of current B cell-targeting therapeutic strategies and may lead to more targeted approaches.

Effect of genome and environment on metabolic and inflammatory profiles

Twin and family studies have established the contribution of genetic factors to variation in metabolic, hematologic and immunological parameters. The majority of these studies analyzed single or combined traits into pre-defined syndromes. In the present study, we explore an alternative multivariate approach in which a broad range of metabolic, hematologic, and immunological traits are analyzed simultaneously to determine the resemblance of monozygotic (MZ) twin pairs, twin-spouse pairs and unrelated, non-cohabiting individuals. A total of 517 participants from the Netherlands Twin Register, including 210 MZ twin pairs and 64 twin-spouse pairs, took part in the study. Data were collected on body composition, blood pressure, heart rate, and multiple biomarkers assessed in fasting blood samples, including lipid levels, glucose, insulin, liver enzymes, hematological measurements and cytokine levels. For all 51 measured traits, pair-wise Pearson correlations, correcting for family relatedness, were calculated across all the individuals in the cohort. Hierarchical clustering techniques were applied to group the measured traits into sub-clusters based on similarity. Sub-clusters were observed among metabolic traits and among inflammatory markers. We defined a phenotypic profile as the collection of all the traits measured for a given individual. Average within-pair similarity of phenotypic profiles was determined for the groups of MZ twin pairs, spouse pairs and pairs of unrelated individuals. The average similarity across the full phenotypic profile was higher for MZ twin pairs than for spouse pairs, and lowest for pairs of unrelated individuals. Cohabiting MZ twins were more similar in their phenotypic profile compared to MZ twins who no longer lived together. The correspondence in the phenotypic profile is therefore determined to a large degree by familial, mostly genetic, factors, while household factors contribute to a lesser degree to profile similarity.

Resequencing of nicotinic acetylcholine receptor genes and association of common and rare variants with the Fagerström test for nicotine dependence

Common single-nucleotide polymorphisms (SNPs) at nicotinic acetylcholine receptor (nAChR) subunit genes have previously been associated with measures of nicotine dependence. We investigated the contribution of common SNPs and rare single-nucleotide variants (SNVs) in nAChR genes to Fagerström test for nicotine dependence (FTND) scores in treatment-seeking smokers. Exons of 10 genes were resequenced with next-generation sequencing technology in 448 European-American participants of a smoking cessation trial, and CHRNB2 and CHRNA4 were resequenced by Sanger technology to improve sequence coverage. A total of 214 SNP/SNVs were identified, of which 19.2% were excluded from analyses because of reduced completion rate, 73.9% had minor allele frequencies <5%, and 48.1% were novel relative to dbSNP build 129. We tested associations of 173 SNP/SNVs with the FTND score using data obtained from 430 individuals (18 were excluded because of reduced completion rate) using linear regression for common, the cohort allelic sum test and the weighted sum statistic for rare, and the multivariate distance matrix regression method for both common and rare SNP/SNVs. Association testing with common SNPs with adjustment for correlated tests within each gene identified a significant association with two CHRNB2 SNPs, eg, the minor allele of rs2072660 increased the mean FTND score by 0.6 Units (P=0.01). We observed a significant evidence for association with the FTND score of common and rare SNP/SNVs at CHRNA5 and CHRNB2, and of rare SNVs at CHRNA4. Both common and/or rare SNP/SNVs from multiple nAChR subunit genes are associated with the FTND score in this sample of treatment-seeking smokers.

Analysis and classification of common vegetable oils

The analysis of fatty acids from common vegetable oils was investigated for application to forensic casework. A base-catalyzed transesterification of the fatty acids to fatty acid methyl esters using tetramethylammonium hydroxide was simple, rapid, straightforward and inexpensive. Canola, corn, olive, peanut, safflower, soybean and sunflower oils were able to be classified based on their fatty acid methyl ester profiles. Using gas chromatography-mass spectrometry, the detection limits for canola, corn, olive, peanut and safflower oils were determined to be 0.4 mg/mL or less and 0.2 mg/mL or less for soybean and sunflower oils.